Keywords
Citation
Based on the search results, sociologists define racism in several different ways across various communities of scholarship:
Structural/Institutional Approach: Some sociologists, like Bonilla-Silva, define racism as a structural phenomenon ingrained in society’s institutions and systems, rather than just individual prejudice. This view sees racism as “a structure, a network of relations at social, political, economic, and ideological levels that shapes the life chances of the various races” [1].
Cultural Approach: Other scholars focus on racism as cultural messages, ideologies, and practices that produce and normalize racial inequities. For example, Ibram X. Kendi defines racism as “a marriage of racist policies and racist ideas that produces and normalizes racial inequities” [1].
Individual Attitudes/Psychology Approach: Some earlier definitions focused more on racism as individual-level prejudice, bias, or hostility toward other racial groups. This view sees racism primarily as an individual problem of overt hostility [1].
Group Conflict Approach: Some sociologists view racism as rooted in group-level competition over resources and power between racial groups [1].
Intersectional Approach: Scholars like Patricia Hill Collins examine how racism intersects with other systems of oppression like sexism and classism [1].
“New Racism” Approaches: More recent theories look at subtle, covert forms of racism that persist in an era of declining overt racist attitudes, including concepts like colorblind racism, laissez-faire racism, etc. [1][2]
The analysis by Shiao and Woody (2021) identified six distinct communities of scholars using different meanings and citations related to racism, spanning structural, cultural, and attitudinal conceptions [4]. They found that even though Bonilla-Silva’s structural approach is considered “standard,” it was primarily cited in only one of the six communities they identified.
Overall, while there are some common elements, sociologists continue to debate and refine how to best conceptualize and study racism in contemporary society. The field appears to be moving toward more multidimensional understandings that can capture both overt and subtle manifestations of racism at individual, institutional, and cultural levels.
We conceptualize a comparative systematic review (CSR) method to identify variations in bibliometric data on a topic of study. We focus comparisons on three sample data sets which contains articles on racism in the context of science, technology, engineering, and mathematics. Rather than generate increasingly defined criteria to inform the analysis, we focus on the study index within the bibliographic metadata. We find significant differences in the content and associations in author and keyword data, as well as occurrence networks and study themes. Those themes which occur across data sets are framed as notions, and posiiton as a part of a conceptual replication.
CSR responds to the completeness dilemma in the analysis of bibliographic metadata. As research productivity increases and different lines of study are leveraged across different disciplines, CSR supports researchers in their development of inclusion and exclusion criteria for systematic reviews on increasingly mulitdisiplineary, interdisciplinary, and cross-disciplinary topics of study. We describe the differences of these frameworks as one example to situating the objects of data for a systematic analysis.
We use the term ‘notion’ to examine the driving themes for the study. We examine context-dependent instances of racism that point to broader meanings across two sets of disciplinary outputs, in the education research indices and in science, technology, engineering, and mathematics (STEM) publication indices. We make sense of noticeable differences in the way that scholars have utilized racism across the disciplines and different scholarly outlets.
Beverly Daniel Tatum describes racism as “a system of advantage based on race” and adds that it is “not only a personal ideology based on racial prejudice, but a system involving cultural messages and institutional policies and practices as well as the beliefs and actions of individuals” (Tatum, 1997, p. 7).
Ruth Wilson Gilmore defines racism as “the state-sanctioned or extralegal production and exploitation of group-differentiated vulnerability to premature death” (Gilmore, 2007, p. 28).
Ibram X. Kendi defines racism as “a marriage of racist policies and racist ideas that produces and normalizes racial inequities” (Kendi, 2019, p. 18).
Racism is a structure, a network of relations at social, political, economic, and ideological levels that shapes the life chances of the various races (Bonilla-Silva, 2013, p. 26)
This study is motivated, in part, by the work of Shiao & Woody (2021) who discuss the various meanings of racism in sociological journal content. For the purpose of this study, our team sought to make sense of the nature of this intellectual structure in STEM, and the various concepts and themes that are situated within this structure.
| Bonilla-Silva | Shiao and Woody |
|---|---|
| A: Pyschological | A: Individual attitudes |
| B: Cultural | B: Cultural schema |
| C: Structural | C\(_1\): Structural: Pre-existing conditions |
| C\(_2\): Structural: Create or maintain | |
| C\(_3\): Structural: Spatial |
Data source: Clariate Analytics Web of Science
Data format: Plain text
Time span: 2003 - 2023
Document Type: Articles; Articles, early access
Query date: July 1, 2024
What is the state of the intellectual structure and emerging notions in research on racism in STEM?
We integrate systematic review techniques with computational methods to generate the methods for the study. The systematic review process builds on qualitative meta-synthesis techniques, as well as content and thematic analysis. The computational methods follow the general scientific mapping workflow for working with large sets of citations data.
We conducted a replication of the Shian & Woody study. Study details were obtained from the original article, as well as cited or related articles, to ensure a set of steps for the conceptual replication were derived. The initial search for articles from the Web of Science Core Collection included the query (((TI=(racism or racist)) OR AB=(racism or racist)) OR AK=(racism or racist)) AND DOP=(1995-01-01/2015-12-31)) AND LA=(English) returned 8,950 results. When the article requirement and individual collection indices were added (SSCI, A&HCI, ESCI, and SCI-EXPANDED), a total of 6,378 articles remained. When the results were subset to those indexed as Sociology, a total of 1,033 articles remained.
(TI=(racism or racist) OR AB=(racism or racist) OR AK=(racism or racist)) AND DOP=(1995-01-01/2015-12-31) AND LA=(English)
The search results returned a total of 1,430 articles, four less than the original study. The results were not able to duplicated was likely an issue of database updates. These changes were within an appropriate range to proceed.
When education journal indexed articles were selected, a total of 853 results remained. https://www.webofscience.com/wos/woscc/summary/bfe60ccd-86c6-40d0-9ba5-16b667ff199e-f83fbe53/relevance/1
When science, technology, engineering, and mathematical indexed subjects were selected a total of 1,462 results remained. https://www.webofscience.com/wos/woscc/summary/eff6a28e-2893-454e-a79f-13e94a7d6c0e-f83fba7d/relevance/1
Forty results were returned when the sample is subset to education journal articles including one of the terms science, technology, engineering, mathematics, or STEM in their title or abstract. https://www.webofscience.com/wos/woscc/summary/d5c643f1-25c7-46c1-93ef-6f458652d262-f83fe3c7/relevance/1
Four databases were used initially to identify the possible collections of sources, and to compare the various results obtained across databases: ERIC, Google Scholar, Scopus, and Web of Science.
ERIC.
Scopus.
Google Scholar.
We noticed across these other databases which provide APIs to support the easy access to bibliometric data that variation would be a concern. As a result, we proceeded further with the conceptual replication by using the Web of Science Core Collection of bibliometric data. This selection provided us with an opportunity to examine one of the main goals of the study, which was to understand differences across disciplinary boundaries despite the increasingly interdisciplinary nature of the research on racism in STEM.
Web of Science (WoS). The WoS Core Collection was used to obtain bibliographic information for the study sample. The Science Citation Index Expanded (SCI-EXPANDED), Social Science Citation Index (SSCI), Arts & Humanities Citation Index (ACHI), and Emerging Sources Citation Index (ESCI) were selected. The Conference Proceedings Citation Index - Science (CPCI-S), Conference Proceedings Citation Index - Social Science (CPCI-SSH), Book Citaton Index - Science (BKCI-S), and Book Citation Index - Social Science & Humanities (BKCI-SSH) were not selected. Given the formal inclusion of psychology as one of the STEM disciplines by research foundations, such as the National Science Foundation (NSF) in the United States, social science bibliographic entries were included in the second sample.
[Query link]{https://www.webofscience.com/wos/woscc/summary/6d0d4c0d-2e83-4162-bd8f-077ad0a4cc34-f7d6e8a1/relevance/1}
Year: 2003-2023
A final total analytic sample of 351 articles was selected for inclusion in the study.
These articles included the words racism or racist in their abstracts and at least one of the terms, science, technology, engineering, mathematics, or STEM in their abstracts); the time period was expanded to include article for the 20 year period from 2003 to 2023. https://www.webofscience.com/wos/woscc/summary/331dedce-0c5c-40cd-b63e-734077ea3736-f840d6cf/relevance/1
This expansion was based on the social contexts of major research outputs across science and mathematics education. Namely, the social turn in mathematics education was published in 2000. No Child Left Behind Act was enacted in 2001. There was also a spike in research productivity identified in the study samples during the cleaning and initial analysis (which included all years) for the specific period between 2000 and 2003.
Final data analysis was run on July 3, 2024.
Prior to this period, multiple programs were designed and checked to ensure accuracy across different samples and generated psuedo data. All programs were confirmed to return the same results across studies.
3,318,115 results from Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Arts & Humanities Citation Index (A&HCI), Emerging Sources Citation Index (ESCI): for ABSTRACT AND racism or science or technology or engineering or mathematics or stem https://www.webofscience.com/wos/woscc/summary/b7144fe8-2337-4d15-b2db-0fc78da08022-f78ebcfe/relevance/1
Load packages and libraries; import for data analysis.
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## Attaching package: 'dplyr'
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
## here() starts at /Users/nathanalexander/Dropbox/Projects/racism-stem-ed
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## here() starts at /Users/nathanalexander/Dropbox/Projects/racism-stem-ed/reports
Bibliometrix## Please note that our software is open source and available for use, distributed under the MIT license.
## When it is used in a publication, we ask that authors properly cite the following reference:
##
## Aria, M. & Cuccurullo, C. (2017) bibliometrix: An R-tool for comprehensive science mapping analysis,
## Journal of Informetrics, 11(4), pp 959-975, Elsevier.
##
## Failure to properly cite the software is considered a violation of the license.
##
## For information and bug reports:
## - Take a look at https://www.bibliometrix.org
## - Send an email to info@bibliometrix.org
## - Write a post on https://github.com/massimoaria/bibliometrix/issues
##
## Help us to keep Bibliometrix and Biblioshiny free to download and use by contributing with a small donation to support our research team (https://bibliometrix.org/donate.html)
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## To start with the Biblioshiny app, please digit:
## biblioshiny()
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## Converting your wos collection into a bibliographic dataframe
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## Done!
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## Generating affiliation field tag AU_UN from C1: Done!
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## Generating affiliation field tag AU_UN from C1: Done!
We use the duplicatedMatching() function and code
suggestion to test for and remove any duplicate records in the
bibliometric data. When duplicate records are noted, the data new data
frame is used as the main object.
M1_dup <- duplicatedMatching(M1, Field = "ID", exact=FALSE, tol = 0.95)
dim(M1)
## [1] 508 61
dim(M1_dup)
## [1] 278 61
M2_dup <- duplicatedMatching(M2, Field = "ID", exact=FALSE, tol = 0.95)
dim(M2)
## [1] 228 61
dim(M2_dup)
## [1] 132 61
M3_dup <- duplicatedMatching(M3, Field = "TI", exact=FALSE, tol = 0.95)
dim(M3)
## [1] 736 61
dim(M3_dup)
## [1] 351 61
# the package developer noted that when using `duplicatedMatching` we get missing data that is required later in the analysis. I have worked around this issue by changing the Field from "TI" to "ID". While this tempoararily supports the analysis, a fix should be found to retain the bibliometric data from the ID columns as downloaded from WoS.
There was an issue with the code, so it was fixed using the
janitor() functions.
##
## Attaching package: 'janitor'
## The following objects are masked from 'package:stats':
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## chisq.test, fisher.test
## column_name M1 M1_dup
## 1 AB character character
## 2 AF character character
## 3 AR character character
## 4 AU character character
## 5 AU_UN character character
## 6 AU_UN_NR logical logical
## 7 AU1_UN character character
## 8 BP character character
## 9 C1 character character
## 10 C1raw character character
## 11 C3 character character
## 12 CA character character
## 13 CR character character
## 14 DA character character
## 15 DB character character
## 16 DE character character
## 17 DI character character
## 18 DT character character
## 19 EA character character
## 20 EF character character
## 21 EI character character
## 22 EM character character
## 23 EP character character
## 24 ER character character
## 25 FU character character
## 26 FX character character
## 27 GA character character
## 28 ID character character
## 29 IS character character
## 30 J9 character character
## 31 JI character character
## 32 LA character character
## 33 NR character character
## 34 OA character character
## 35 OI character character
## 36 PA character character
## 37 PD character character
## 38 PG character character
## 39 PI character character
## 40 PM character character
## 41 PT character character
## 42 PU character character
## 43 PY numeric numeric
## 44 RI character character
## 45 RP character character
## 46 SC character character
## 47 SI character character
## 48 SN character character
## 49 SO character character
## 50 SR character character
## 51 SR_FULL character character
## 52 SU character character
## 53 TC numeric numeric
## 54 TI character character
## 55 U1 character character
## 56 U2 character character
## 57 UT character character
## 58 VL character character
## 59 WC character character
## 60 WE character character
## 61 Z9 character character
## column_name M2 M2_dup
## 1 AB character character
## 2 AF character character
## 3 AR character character
## 4 AU character character
## 5 AU_UN character character
## 6 AU_UN_NR logical logical
## 7 AU1_UN character character
## 8 BP character character
## 9 C1 character character
## 10 C1raw character character
## 11 C3 character character
## 12 CA character character
## 13 CR character character
## 14 DA character character
## 15 DB character character
## 16 DE character character
## 17 DI character character
## 18 DT character character
## 19 EA character character
## 20 EF character character
## 21 EI character character
## 22 EM character character
## 23 EP character character
## 24 ER character character
## 25 FU character character
## 26 FX character character
## 27 GA character character
## 28 ID character character
## 29 IS character character
## 30 J9 character character
## 31 JI character character
## 32 LA character character
## 33 NR character character
## 34 OA character character
## 35 OI character character
## 36 PA character character
## 37 PD character character
## 38 PG character character
## 39 PI character character
## 40 PM character character
## 41 PT character character
## 42 PU character character
## 43 PY numeric numeric
## 44 RI character character
## 45 RP character character
## 46 SC character character
## 47 SI character character
## 48 SN character character
## 49 SO character character
## 50 SR character character
## 51 SR_FULL character character
## 52 SU character character
## 53 TC numeric numeric
## 54 TI character character
## 55 U1 character character
## 56 U2 character character
## 57 UT character character
## 58 VL character character
## 59 WC character character
## 60 WE character character
## 61 Z9 character character
## column_name M3 M3_dup
## 1 AB character character
## 2 AF character character
## 3 AR character character
## 4 AU character character
## 5 AU_UN character character
## 6 AU_UN_NR logical logical
## 7 AU1_UN character character
## 8 BP character character
## 9 C1 character character
## 10 C1raw character character
## 11 C3 character character
## 12 CA character character
## 13 CR character character
## 14 DA character character
## 15 DB character character
## 16 DE character character
## 17 DI character character
## 18 DT character character
## 19 EA character character
## 20 EF character character
## 21 EI character character
## 22 EM character character
## 23 EP character character
## 24 ER character character
## 25 FU character character
## 26 FX character character
## 27 GA character character
## 28 ID character character
## 29 IS character character
## 30 J9 character character
## 31 JI character character
## 32 LA character character
## 33 NR character character
## 34 OA character character
## 35 OI character character
## 36 PA character character
## 37 PD character character
## 38 PG character character
## 39 PI character character
## 40 PM character character
## 41 PT character character
## 42 PU character character
## 43 PY numeric numeric
## 44 RI character character
## 45 RP character character
## 46 SC character character
## 47 SI character character
## 48 SN character character
## 49 SO character character
## 50 SR character character
## 51 SR_FULL character character
## 52 SU character character
## 53 TC numeric numeric
## 54 TI character character
## 55 U1 character character
## 56 U2 character character
## 57 UT character character
## 58 VL character character
## 59 WC character character
## 60 WE character character
## 61 Z9 character character
A total of three data frames were used for the study analysis.
The status of the DE (Keyword) category is labeled as
Poor given that 62 missing counts (prop=0.2375) are listed;
however, the ID (Keywords plus) category is listed as
Acceptable, with only 30 missing counts (prop=0.1149). All
other indicators are listed as Good (at least 1 missing
count) or Excellent (0 missing counts).
dim(M1_dup)
## [1] 278 61
head(M1_dup, n = 2)
## AU
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE EO
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS TC;MORTON K
## AF
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE, EBONY OMOTOLA
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS, TIA C.;MORTON, KARISMA
## CR
## MCGEE EO, 2020, EDUC RESEARCHER ADSERIAS RP, 2017, RACE ETHNIC EDUC-UK, V20, P315, DOI 10.1080/13613324.2016.1260233;ALEXANDER QR, 2016, J DIVERS HIGH EDUC, V9, P307, DOI 10.1037/A0039705;ALLEN A. M., 2017, DOCTORAL DISSERTATION;ANDERSON E.L., 2018, THE 2018 STATUS REPORT ON ENGINEERING EDUCATION: A SNAPSHOT OF DIVERSITY IN DEGREES CONFERRED IN ENGINEERING;ANONYMOUS, 2017, RACISM RACISTS COLOR;ANONYMOUS, 2019, UNCF LAUNCH PROT OUR;ANONYMOUS, 2017, HBCUS MAK AM STRONG;AREVALO I, 2016, J LAT EDUC, V15, P3, DOI 10.1080/15348431.2015.1045143;ASSARI S, 2018, SOC ISS POLICY REV, V12, P112, DOI 10.1111/SIPR.12042;ASSOCIATED PRESS, 2018, ASSOCIATED PRESS;BABER LD, 2015, REV HIGH EDUC, V38, P251;BAILEY ZD, 2017, LANCET, V389, P1453, DOI 10.1016/S0140-6736(17)30569-X;BASILE V, 2015, SCI EDUC, V99, P519, DOI 10.1002/SCE.21156;BATTEY D., 2016, J URBAN MATH ED, V9, P49, DOI DOI 10.21423/JUME-V9I2A294;BENJAMIN R., 2019, RACE TECHNOLOGY ABOL, DOI DOI 10.1145/3290605.3300528;BENJAMIN R, 2016, ETHNIC RACIAL STUD, V39, P2227, DOI 10.1080/01419870.2016.1202423;BERTRAND JONEST., 2015, INT J DOCTORAL STUDI, V10, P483, DOI DOI 10.28945/2305;BONILLA-SILVA E, 2015, AM BEHAV SCI, V59, P1358, DOI 10.1177/0002764215586826;BONILLA-SILVA E, 2011, ANN AM ACAD POLIT SS, V634, P190, DOI 10.1177/0002716210389702;BONILLA-SILVA EDUARDO., 2001, WHITE SUPREMACY AND RACISM IN THE POST-CIVIL RIGHTS ERA;BORNSTEIN A., 2017, NAUTILUS DEC. 21;BOYKIN T. F., 2017, PROFESSIONAL ED HIST;BRADLEY J., 2019, GOOD SCI ENG RES ENT;BROOMS DR, 2018, CRIT SOCIOL, V44, P141, DOI 10.1177/0896920516658940;BROWN BA, 2017, URBAN EDUC, V52, P170, DOI 10.1177/0042085916661385;BROWN BA, 2016, J RES SCI TEACH, V53, P146, DOI 10.1002/TEA.21249;BROWN SIMONE, 2015, DARK MATTERS: ON THE SURVEILLANCE OF BLACKNESS;BRUNSMA DL, 2017, SOCIOL RACE ETHNIC, V3, P1, DOI 10.1177/2332649216681565;BULLOCK EC, 2017, EDUC STUD-AESA, V53, P628, DOI 10.1080/00131946.2017.1369082;BUOLAMWINI J., 2016, TEDX BEACON STREET;BUOLAMWINI JOY, 2018, NEW YORK TIMES;BURT BA, 2019, AM EDUC RES J, V56, P39, DOI 10.3102/0002831218789595;BURT BA, 2018, AM EDUC RES J, V55, P965, DOI 10.3102/0002831218763587;BYARS-WINSTON A, 2014, CAREER DEV Q, V62, P340, DOI 10.1002/J.2161-0045.2014.00087.X;CAMPBELL TA., 2016, CAREER TECHNICAL ED, V41, P85, DOI DOI 10.5328/CTER41.2.85;CANNADY MA, 2014, SCI EDUC, V98, P443, DOI 10.1002/SCE.21108;CARLONE HB, 2007, J RES SCI TEACH, V44, P1187, DOI 10.1002/TEA.20237;CARLSON J., 2019, CBS 46 0926;CARTER D.F., 2019, HIGHER EDUCATION: HANDBOOK OF THEORY AND RESEARCH: VOLUME, V34, P39, DOI DOI 10.1007/978-3-030-03457-32, DOI 10.1007/978-3-030-03457-3_2, 10.1007/978-3-030-03457-3_2;COLLINS KH, 2018, J ADV ACAD, V29, P143, DOI 10.1177/1932202X18757958;COUTS A., 2011, DIGITAL TRENDS 0526;CURTIS S., 2017, MIRROR 1222;DARITY W, 2021, CONTEMP ECON POLICY, V39, P494, DOI 10.1111/COEP.12476;DAVID E.J.R., 2017, PSYCHOL OPPRESSION;DOUGAL C, 2019, J FINANC ECON, V134, P570, DOI 10.1016/J.JFINECO.2019.05.010;ENGELS D. 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## MADKINS TC, 2021, CAN J SCI MATH TECHN AGUIRRE J., 2013, THE IMPACT OF IDENTITY IN K-8 MATHEMATICS: RETHINKING EQUITY-BASED PRACTICES;ANNAMMA S, 2018, TEACH TEACH EDUC, V73, P70, DOI 10.1016/J.TATE.2018.03.008;ANNAMMA SA, 2013, RACE ETHNIC EDUC-UK, V16, P1, DOI 10.1080/13613324.2012.730511;ANONYMOUS, 2016, STAMPED BEGINNING DE;ANONYMOUS, 2007, LEARNING OUT SCH DIV;ANONYMOUS, 2012, RACE DECODED GENOMIC;ANONYMOUS, 2016, THE NATION'S REPORT CARD;BANG, 2020, TRUTHOUT ED YOUTH OP;BANG M., 2017, HELPING STUDENTS MAK, P33, DOI DOI 10.2505/9781938946042;BANG M, 2020, COGNITION INSTRUCT, V38, P434, DOI 10.1080/07370008.2020.1777999;BANG M, 2015, J RES SCI TEACH, V52, P530, DOI 10.1002/TEA.21204;BARTOLOME LI, 1994, HARVARD EDUC REV, V64, P173, DOI 10.17763/HAER.64.2.58Q5M5744T325730;BEAUBOEUF-LAFONTANT T, 1999, TEACH COLL REC, V100, P702, DOI 10.1111/0161-4681.00013;BELL DA, 1995, U ILLINOIS LAW REV, P893;BENNETT, 2020, POLICY OPTIONS POLIT;BLISS C, 2015, ANN AM ACAD POLIT SS, V661, P86, DOI 10.1177/0002716215587687;BLOCK D., 2020, WASH MON;BOSTON, 2018, REHUMANIZING MATH BL;BOUTTE G., 2010, INTERNATIONAL JOURNAL OF MULTICULTURAL EDUCATION, V12, DOI 10.18251/IJME.V12I2.343;BRAYBOY BRYANMCKINLEY JONES., 2006, THE URBAN REVIEW, V37, P425, DOI DOI 10.1007/S11256-005-0018-Y, HTTPS://DOI.ORG/10.1007/S11256-005-0018-Y;BROWN B.A., 2019, SCI CITY CULTURALLY;BULLOCK EC, 2017, EDUC STUD-AESA, V53, P628, DOI 10.1080/00131946.2017.1369082;BARTON AC, 2020, EDUC RESEARCHER, V49, P433, DOI 10.3102/0013189X20927363;CARTER PRUDENCEL., 2014, INEQUALITY MATTERS;CEDILLO S, 2018, CAN J SCI MATH TECHN, V18, P242, DOI 10.1007/S42330-018-0025-0;CENT. 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## AB
## MCGEE EO, 2020, EDUC RESEARCHER THE RACIALIZED STRUCTURE OF STEM (SCIENCE, TECHNOLOGY, ENGINEERING, MATHEMATICS) HIGHER EDUCATION MAINTAINS GROSS INEQUITIES THAT ARE ILLUSTRATIVE OF STRUCTURAL RACISM, WHICH BOTH INFORMS AND IS REINFORCED BY DISCRIMINATORY BELIEFS, POLICIES, VALUES, AND DISTRIBUTION OF RESOURCES. THUS, AN EXAMINATION INTO STRUCTURAL RACISM IN STEM IS NEEDED TO EXPOSE THE MARGINALIZATION OF UNDERREPRESENTED GROUPS IN STEM AND TO IMPROVE UNDERSTANDING OF THE STEM POLICIES, PRACTICES, AND PROCEDURES THAT ALLOW THE FOUNDATION OF RACISM TO REMAIN INTACT. I ARGUE THAT, EVEN AT THE TOP OF THE EDUCATION HIERARCHY, BLACK STEM DOCTORATE STUDENTS AND PHD DEGREE HOLDERS CONSISTENTLY ENDURE THE RACIST RESIDUE OF HIGHER EDUCATION INSTITUTIONS AND STEM EMPLOYERS. THUS, THIS MANUSCRIPT ALSO DISCUSSES HOW UNIVERSITIES INSTITUTIONALIZE DIVERSITY MENTORING PROGRAMS DESIGNED MOSTLY TO FIX (READ "ASSIMILATE") UNDERREPRESENTED STUDENTS OF COLOR WHILE IGNORING OR MINIMIZING THE ROLE OF THE STEM DEPARTMENTS IN CREATING RACIALLY HOSTILE WORK AND EDUCATIONAL SPACES. I ARGUE THAT, WITHOUT A CRITICAL EXAMINATION OF THE STRUCTURAL RACISM OMNIPRESENT IN THE STEM, PROGRESS IN RACIALLY DIVERSIFYING STEM WILL CONTINUE AT A SNAIL'S PACE.
## MADKINS TC, 2021, CAN J SCI MATH TECHN IF WE ENVISION A FUTURE FOR BLACK YOUNG LEARNERS WHERE THEIR FULL HUMANITY IS HONOURED AND EDUCATORS FACILITATE RIGOROUS SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) LEARNING EXPERIENCES THAT ARE JUSTICE-FOCUSED, WE MUST DISRUPT SYSTEMIC RACISM NOW. IN THIS ARTICLE WE DISCUSS HOW ANTI-BLACKNESS IS PERVASIVE IN SCIENCE AND MATHEMATICS EDUCATION, ESPECIALLY FOR YOUNG LEARNERS. WE ALSO ADDRESS WHY TEACHER EDUCATORS MUST DISRUPT ANTI-BLACK RACISM IN OUR WORK WITH ELEMENTARY TEACHER CANDIDATES AND IN OUR RESEARCH. WE ARGUE THAT TO DO THIS WORK AND DISRUPT ANTI-BLACKNESS, ELEMENTARY TEACHER EDUCATORS AND TEACHER CANDIDATES NEED POLITICAL CLARITY (BEAUBOEUF-LAFONTANT, 1999). POLITICAL CLARITY IS THE UNDERSTANDING OF HOW STRUCTURAL AND SCHOOL INEQUALITIES WORK TO (RE)PRODUCE DIFFERENTIAL LEARNING EXPERIENCES FOR MINORITIZED LEARNERS. WE OFFER SUGGESTIONS FOR HOW TEACHER EDUCATORS CAN FURTHER DEVELOP THEIR TEACHER CANDIDATES' POLITICAL CLARITY. DRAWING UPON OUR PRIOR RESEARCH, COURSE ASSIGNMENTS, AND EXPERIENCES AS BLACK WOMEN EDUCATORS AND TEACHER EDUCATORS, WE SHARE EXAMPLES OF HOW AN INDIVIDUAL'S POLITICAL CLARITY CAN BE DEVELOPED WITHIN SCIENCE AND MATHEMATICS METHODS COURSES. IN DOING SO, WE BUILD UPON PRIOR RESEARCH IN STEM TEACHER EDUCATION ON HOW TEACHERS COME TO SEE TEACHING AS A POLITICAL ACT AND ENGAGE IN THE HARD WORK OF EQUITY-FOCUSED STEM TEACHING.
## AR BP
## MCGEE EO, 2020, EDUC RESEARCHER <NA> 633
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA> 239
## C1
## MCGEE EO, 2020, EDUC RESEARCHER VANDERBILT UNIV, DIVERS & STEM EDUC, PEABODY COLL, PMB 230 GPC 230 APPLETON PL, NASHVILLE, TN 37203 USA.;
## MADKINS TC, 2021, CAN J SCI MATH TECHN UNIV TEXAS AUSTIN, COLL EDUC, 1912 SPEEDWAY,STOP D5500, AUSTIN, TX 78712 USA.; UNIV NORTH TEXAS, COLL EDUC, 1155 UNION CIRCLE, DENTON, TX 76203 USA.;
## C3
## MCGEE EO, 2020, EDUC RESEARCHER VANDERBILT UNIVERSITY; VANDERBILT UNIVERSITY PEABODY COLLEGE
## MADKINS TC, 2021, CAN J SCI MATH TECHN UNIVERSITY OF TEXAS SYSTEM; UNIVERSITY OF TEXAS AUSTIN; UNIVERSITY OF NORTH TEXAS SYSTEM; UNIVERSITY OF NORTH TEXAS DENTON
## CA DA
## MCGEE EO, 2020, EDUC RESEARCHER <NA> 2024-07-01
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA> 2024-07-01
## DE
## MCGEE EO, 2020, EDUC RESEARCHER CULTURAL ANALYSIS; DISPARITIES; DOCTORAL; ENGINEERING EDUCATION; ENTREPRENEURSHIP; HBCUS; HIGHER EDUCATION; MENTORING; MINORITIZED; RACE; STEM; STRUCTURAL RACISM; TECHNOLOGY
## MADKINS TC, 2021, CAN J SCI MATH TECHN ANTI-BLACKNESS; ANTI-RACIST TEACHING; EQUITY; POLITICAL CLARITY; ELEMENTARY STEM EDUCATION
## DI DT
## MCGEE EO, 2020, EDUC RESEARCHER 10.3102/0013189X20972718 ARTICLE
## MADKINS TC, 2021, CAN J SCI MATH TECHN 10.1007/s42330-021-00159-1 ARTICLE
## EA EF EI
## MCGEE EO, 2020, EDUC RESEARCHER <NA> <NA> 1935-102X
## MADKINS TC, 2021, CAN J SCI MATH TECHN AUG 2021 <NA> 1942-4051
## EM EP ER FU
## MCGEE EO, 2020, EDUC RESEARCHER EBONY.MCGEE@VANDERBILT.EDU 644 <NA>
## MADKINS TC, 2021, CAN J SCI MATH TECHN TMADKINS@AUSTIN.UTEXAS.EDU 256 <NA>
## FX GA
## MCGEE EO, 2020, EDUC RESEARCHER <NA> OZ1OY
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA> UI9TW
## ID
## MCGEE EO, 2020, EDUC RESEARCHER MATHEMATICS EDUCATION; COLOR; BLACK; RACE; SCIENCE; IDENTITY; STUDENTS; HEALTH; WOMEN; EXPERIENCES
## MADKINS TC, 2021, CAN J SCI MATH TECHN CRITICAL RACE THEORY; PEDAGOGY; STORIES; EQUITY; AGENCY
## IS J9
## MCGEE EO, 2020, EDUC RESEARCHER 9 EDUC RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN 2 CAN J SCI MATH TECHN
## JI
## MCGEE EO, 2020, EDUC RESEARCHER EDUC. RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN CAN. J. SCI. MATH. TECHNOL. EDUC.
## LA NR OA
## MCGEE EO, 2020, EDUC RESEARCHER ENGLISH 116 BRONZE
## MADKINS TC, 2021, CAN J SCI MATH TECHN ENGLISH 103 BRONZE
## OI
## MCGEE EO, 2020, EDUC RESEARCHER <NA>
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS, TIA/0000-0002-2555-9025; MORTON, KARISMA/0000-0003-1054-3554
## PA
## MCGEE EO, 2020, EDUC RESEARCHER 2455 TELLER RD, THOUSAND OAKS, CA 91320 USA
## MADKINS TC, 2021, CAN J SCI MATH TECHN ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
## PD PG PI PM PT
## MCGEE EO, 2020, EDUC RESEARCHER DEC 12 THOUSAND OAKS <NA> J
## MADKINS TC, 2021, CAN J SCI MATH TECHN JUN 18 NEW YORK 38624762 J
## PU PY
## MCGEE EO, 2020, EDUC RESEARCHER SAGE PUBLICATIONS INC 2020
## MADKINS TC, 2021, CAN J SCI MATH TECHN SPRINGER 2021
## RI
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE, EBONY OMOTOLA/F-1747-2016
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA>
## RP
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE, EO (CORRESPONDING AUTHOR), VANDERBILT UNIV, DIVERS & STEM EDUC, PEABODY COLL, PMB 230 GPC 230 APPLETON PL, NASHVILLE, TN 37203 USA.
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS, TC (CORRESPONDING AUTHOR), UNIV TEXAS AUSTIN, COLL EDUC, 1912 SPEEDWAY,STOP D5500, AUSTIN, TX 78712 USA.
## SC SI
## MCGEE EO, 2020, EDUC RESEARCHER EDUCATION & EDUCATIONAL RESEARCH <NA>
## MADKINS TC, 2021, CAN J SCI MATH TECHN EDUCATION & EDUCATIONAL RESEARCH SI
## SN
## MCGEE EO, 2020, EDUC RESEARCHER 0013-189X
## MADKINS TC, 2021, CAN J SCI MATH TECHN 1492-6156
## SO
## MCGEE EO, 2020, EDUC RESEARCHER EDUCATIONAL RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN CANADIAN JOURNAL OF SCIENCE MATHEMATICS AND TECHNOLOGY EDUCATION
## SU TC
## MCGEE EO, 2020, EDUC RESEARCHER <NA> 171
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA> 22
## TI
## MCGEE EO, 2020, EDUC RESEARCHER INTERROGATING STRUCTURAL RACISM IN STEM HIGHER EDUCATION
## MADKINS TC, 2021, CAN J SCI MATH TECHN DISRUPTING ANTI-BLACKNESS WITH YOUNG LEARNERS IN STEM: STRATEGIES FOR ELEMENTARY SCIENCE AND MATHEMATICS TEACHER EDUCATION
## U1 U2 UT VL
## MCGEE EO, 2020, EDUC RESEARCHER 26 80 WOS:000594705200001 49
## MADKINS TC, 2021, CAN J SCI MATH TECHN 1 4 WOS:000681587200001 21
## WC
## MCGEE EO, 2020, EDUC RESEARCHER EDUCATION & EDUCATIONAL RESEARCH
## MADKINS TC, 2021, CAN J SCI MATH TECHN EDUCATION, SCIENTIFIC DISCIPLINES
## WE
## MCGEE EO, 2020, EDUC RESEARCHER SOCIAL SCIENCE CITATION INDEX (SSCI)
## MADKINS TC, 2021, CAN J SCI MATH TECHN EMERGING SOURCES CITATION INDEX (ESCI)
## Z9
## MCGEE EO, 2020, EDUC RESEARCHER 239
## MADKINS TC, 2021, CAN J SCI MATH TECHN 27
## C1raw
## MCGEE EO, 2020, EDUC RESEARCHER [MCGEE, EBONY OMOTOLA] VANDERBILT UNIV, DIVERS & STEM EDUC, PEABODY COLL, PMB 230 GPC 230 APPLETON PL, NASHVILLE, TN 37203 USA.
## MADKINS TC, 2021, CAN J SCI MATH TECHN [MADKINS, TIA C.] UNIV TEXAS AUSTIN, COLL EDUC, 1912 SPEEDWAY,STOP D5500, AUSTIN, TX 78712 USA. [MORTON, KARISMA] UNIV NORTH TEXAS, COLL EDUC, 1155 UNION CIRCLE, DENTON, TX 76203 USA.
## DB
## MCGEE EO, 2020, EDUC RESEARCHER ISI
## MADKINS TC, 2021, CAN J SCI MATH TECHN ISI
## AU_UN
## MCGEE EO, 2020, EDUC RESEARCHER VANDERBILT UNIVERSITY; VANDERBILT UNIVERSITY PEABODY COLLEGE
## MADKINS TC, 2021, CAN J SCI MATH TECHN UNIVERSITY OF TEXAS SYSTEM; UNIVERSITY OF TEXAS AUSTIN; UNIVERSITY OF NORTH TEXAS SYSTEM; UNIVERSITY OF NORTH TEXAS DENTON
## AU1_UN AU_UN_NR
## MCGEE EO, 2020, EDUC RESEARCHER VANDERBILT UNIV NA
## MADKINS TC, 2021, CAN J SCI MATH TECHN UNIV TEXAS AUSTIN NA
## SR_FULL
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE EO, 2020, EDUC RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS TC, 2021, CAN J SCI MATH TECHN
## SR
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE EO, 2020, EDUC RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS TC, 2021, CAN J SCI MATH TECHN
dim(M2_dup)
## [1] 132 61
head(M2_dup, n = 2)
## AU
## MOREAU CS, 2022, PATHOG DIS MOREAU CS;DARBY AM;DEMERY AJC;HERNÁNDEZ LMA;MEADERS CL
## O'HARA RM, 2022, J CONSTR PSYCHOL O'HARA RM
## AF
## MOREAU CS, 2022, PATHOG DIS MOREAU, CORRIE S.;DARBY, ANDREA M.;DEMERY, AMELIA-JULIETTE C.;HERNANDEZ, LINA M. ARCILA;MEADERS, CLARA L.
## O'HARA RM, 2022, J CONSTR PSYCHOL O'HARA, ROBERT M.
## CR
## MOREAU CS, 2022, PATHOG DIS ADAMS M., 2016, TEACHING FOR DIVERSITY AND SOCIAL JUSTICE;ALSHEBLI BK, 2018, NAT COMMUN, V9, DOI 10.1038/S41467-018-07634-8;ANDERSON S.K., 2017, BRINGING SCHOOL TO LIFE: PLACE-BASED EDUCATION ACROSS THE CURRICULUM;BENTLEY AR, 2017, J COMMUN GENET, V8, P255, DOI 10.1007/S12687-017-0316-6;BHAGIA A., 2020, DOES RACE BELONG UND;BOOTH JM, 2004, GENETICS, V168, P1111, DOI 10.1534/GENETICS.103.023077;BREWER C, 2011, VISION AND CHANGE IN UNDERGRADUATE BIOLOGY EDUCATION: A CALL TO ACTION;BROOCKMAN D, 2016, SCIENCE, V352, P220, DOI 10.1126/SCIENCE.AAD9713;CAMPBELL LG, 2013, PLOS ONE, V8, DOI 10.1371/JOURNAL.PONE.0079147;CHAPMAN R., 2019, DIVERSIFYING STEM MU, P36;COOPER KATELYN M, 2020, CBE LIFE SCI EDUC, V19, PES6, DOI 10.1187/CBE.20-04-0062;CRENSHAW K., 1989, UNIV CHICAGO LEG FOR, P138;DONOVAN BM., 2021, MORE HUMANE GENETICS;DOUGLASS JA., 2008, CTR STUDIES HIGHER E, V15, P1;ELLIOTT R, 1996, RES HIGH EDUC, V37, P681, DOI 10.1007/BF01792952;FORD FOUNDATION, 2021, DIV EQU INCL ANN REP, P54;FRED HUTCHINSON CANCER RESEARCH CENTER SCIENCE EDUCATION PARTNERSHIP, 2021, RAC RAC GEN;FRIEDMANN T, 2019, GENE THER, V26, P351, DOI 10.1038/S41434-019-0088-1;GOVIER M, 1999, NOTES REC ROY SOC, V53, P203, DOI 10.1098/RSNR.1999.0075;GRAVES J.L., 2019, EVOL EDUC OUTREACH, V12, P1, DOI DOI 10.1186/S12052-019-0110-5;GRUENEWALD DA, 2005, ETHICS POLICY ENV, V8, P261, DOI 10.1080/13668790500348208;HILL WD, 2019, NAT COMMUN, V10, DOI 10.1038/S41467-019-13585-5;HOFSTRA B, 2020, P NATL ACAD SCI USA, V117, P9284, DOI 10.1073/PNAS.1915378117;HOLMAN L, 2018, PLOS BIOL, V16, DOI 10.1371/JOURNAL.PBIO.2004956;HOPPE TA, 2019, SCI ADV, V5, DOI 10.1126/SCIADV.AAW7238;HUBBARD AR, 2017, AM BIOL TEACH, V79, P516, DOI 10.1525/ABT.2017.79.7.516;HUDSON N, 1996, EIGHTEENTH-CENT STUD, V29, P247, DOI 10.1353/ECS.1996.0027;INTERGROUP DIALOGUE PROJECT, 2021, IDP GUID COMM AGR IN;JABBOUR J, 2020, P NATL ACAD SCI USA, V117, P18369, DOI 10.1073/PNAS.2003631117;JIMENEZ MF, 2019, NAT ECOL EVOL, V3, P1030, DOI 10.1038/S41559-019-0911-5;LEAVY S, 2018, 2018 IEEE/ACM 1ST INTERNATIONAL WORKSHOP ON GENDER EQUALITY IN SOFTWARE ENGINEERING (GE 2018), P14;LEE A, 2011, CAREER DEV TRANSIT E, V34, P72, DOI 10.1177/0885728810386591;MA YF, 2019, NATURE, V565, P287, DOI 10.1038/D41586-019-00091-3;MCCLENNEN N., 2020, POWER PLACE AUTHENTI;MCINERNEY P, 2011, ASIA-PAC J TEACH EDU, V39, P3, DOI 10.1080/1359866X.2010.540894;MILLER C, 2020, GENDER SOC, V34, P131, DOI 10.1177/0891243219867917;O'BRIEN LT, 2020, SOC PSYCHOL EDUC, V23, P449, DOI 10.1007/S11218-019-09538-X;PERCEPTION INSTITUTE, 2021, IMPL BIAS EXPL;PRATHER C, 2018, HEALTH EQUITY, V2, P249, DOI 10.1089/HEQ.2017.0045;PUERTAS-MOLERO P, 2018, J CLIN MED, V7, DOI 10.3390/JCM7120524;REESE AJ, 2020, J MICROBIOL BIOL EDU, V21, DOI 10.1128/JMBE.V21I1.1947;REINSVOLD LA, 2012, J SCI TEACH EDUC, V23, P745, DOI 10.1007/S10972-011-9235-2;SARTIN JS, 2004, SOUTH MED J, V97, P500, DOI 10.1097/00007611-200405000-00017;SCHELL CJ, 2020, NAT ECOL EVOL, V4, P1285, DOI 10.1038/S41559-020-1266-7;SIDKY G., 2017, ENGLISH LANGUAGE TEACHING, V10, P179, DOI DOI 10.5539/ELT.V10N5P179;SMITH KA, 2015, CELL STEM CELL, V16, P221, DOI 10.1016/J.STEM.2015.02.012;STAATS C., 2017, STATE SCI IMPLICIT B;STEPHAN NANCY., 1982, THE IDEA OF RACE IN SCIENCE: GREAT BRITAIN 1800-1960;THE PROGRAM ON INTERGROUP RELATIONS, 2008, PROGR INT REL U MICH;TINKER B, 2004, LARA ENGAGING CONTRO;UZUN GO., 2020, INT J PSYCHOSOC REHA, V24, P13;WHITTAKER JOSEPH A, 2015, J UNDERGRAD NEUROSCI EDUC, V13, PA136;WHITTAKER JOSEPH A, 2012, J UNDERGRAD NEUROSCI EDUC, V11, PA44;WOODHOUSE J.L., 2000, CLEARINGHOUSE RURAL, P1;ZUNIGA X., 2003, CAMPUS, P8, DOI DOI 10.1177/108648220300700603;ZUNIGA X, 2007, INTERGROUP DIALOGUE, P1
## O'HARA RM, 2022, J CONSTR PSYCHOL ALCOFF LINDAMARTIN., 2003, THE JOURNAL OF ETHICS, V7, P5;ANDRÉS MA, 2017, EUR TRANSP;BABER LD, 2015, REV HIGH EDUC, V38, P251;BANCROFT SF, 2018, SCI EDUC, V102, P1319, DOI 10.1002/SCE.21474;BENTLEY ML, 2017, CRIT EDUC, V8, P1;BONDI S, 2012, J STUD AFF RES PRACT, V49, P397, DOI 10.1515/JSARP-2012-6381;BONILLA-SILVA EDUARDO, 2006, RACISM WITHOUT RACISTS: COLOR-BLIND RACISM AND THE PERSISTENCE OF RACIAL INEQUALITY IN THE UNITED STATES, V2ND, DOI DOI 10.5860/CHOICE.51.09.1531D;BOTTIA MC, 2015, TEACH COLL REC, V117;BRONFENBRENNER U., 2005, MAKING HUMAN BEINGS, P3, DOI DOI 10.1016/J.PEDN.2017.06.013;CABELLO E, 2002, REAL-TIME IMAGING, V8, P1, DOI 10.1006/RTIM.2000.0255;CHAVEZ A.F. S.D. LONGERBEAM., 2016, TEACHING ACROSS CULTURAL STRENGTHS: A GUIDE TO BALANCING INTEGRATED AND INDIVIDUATED CULTURAL FRAMEWORKS IN COLLEGE TEACHING;COLE RM, 2020, POLICY FUTURES EDUC, V18, P90, DOI 10.1177/1478210318767459;COPELAND KJ, 2011, J COLL STUD RETENT-R, V12, P485, DOI 10.2190/CS.12.4.F;CRENSHAW K, 1993, STANFORD LAW REVIEW VOL 43, NO 6, JULY 1991, P1241;CROMLEY J.G., 2016, POLICY INSIGHTS FROM THE BEHAVIORAL AND BRAIN SCIENCES, V3, P4, DOI DOI 10.1177/2372732215622648;DESHLER J, 2019, INT J RES UN MATH ED, V5, P337, DOI 10.1007/S40753-019-00096-3;DONNOR J.K., 2013, HDB CRITICAL RACE TH, P195;DUDZIAK M.L., 2009, FOUNDATIONS OF CRITICAL RACE THEORY IN EDUCATION, P85;FRANKENBERG E., 2018, J LAW ED, V47, P189;GEISINGER BN, 2013, INT J ENG EDUC, V29, P914;GROSSMAN JM, 2014, URBAN EDUC, V49, P698, DOI 10.1177/0042085913481364;HEATH S., 1982, DOING ETHNOGRAPHY SC, P102;INGRAM D., 2012, THESIS;KRANZFELDER P, 2019, INT J SCI EDUC, V41, P1944, DOI 10.1080/09500693.2019.1649503;LADSON-BILLINGS G., 2010, INTERNATIONAL JOURNAL OF QUALITATIVE STUDIES IN EDUCATION, V11, P7, DOI DOI 10.1080/095183998236863;LADSON-BILLINGS G, 2012, EDUC RESEARCHER, V41, P115, DOI 10.3102/0013189X12440743;LADSONBILLINGS G, 1995, TEACH COLL REC, V97, P47;LIU A, 2011, HIGH EDUC, V62, P383, DOI 10.1007/S10734-010-9394-7;LÓPEZ GR, 2014, EDUC ADMIN QUART, V50, P796, DOI 10.1177/0013161X14551410;LOPEZ IAN., 2006, WHITE BY LAW;MADRIGAL-GARCIA Y.I., 2016, J HISPANIC HIGHER ED, V15, P154, DOI DOI 10.1177/1538192716629192;MALCOM S., 2016, BARRIERS OPPORTUNITI, DOI DOI 10.17226/21739;MASLOW A., 1954, MOTIVATION PERSONALI, DOI DOI 10.1037/H0039764;NGUYEN DH, 2021, J ASIAN ARCHIT BUILD, V20, P179, DOI 10.1080/13467581.2020.1782211;NICHOLS S.L., 2007, HIGH STAKES TESTING;O'HARA R M., 2020, P 2020 ANN AM SOC EN;OWENS D.S., 2007, PHILOS SOCIAL CRITIC, V33, P203, DOI DOI 10.1177/0191453707074139;PULLIAM RM, 2017, J SOC WORK EDUC, V53, P414, DOI 10.1080/10437797.2016.1275896;RODRIGUEZ SL, 2021, J DIVERS HIGH EDUC, V14, P441, DOI 10.1037/DHE0000176;SOLORZANO DANIEL G., 2002, QUALITATIVE INQUIRY, V8, P23;STOVALL D, 2016, URBAN EDUC, V51, P274, DOI 10.1177/0042085915618718;STRAYHORN TL, 2012, COLLEGE STUDENTS' SENSE OF BELONGING: A KEY TO EDUCATIONAL SUCCESS FOR ALL STUDENTS, P1;STRAYHORN T.L., 2015, WESTERN JOURNAL OF BLACK STUDIES, V39, P45;TABER K.S., 2016, HANDBOOK OF RESEARCH ON APPLIED LEARNING THEORY AND DESIGN IN MODERN EDUCATION ADVANCES IN EDUCATIONAL TECHNOLOGIES AND INSTRUCTIONAL DESIGN, P116, DOI DOI 10.4018/978-1-4666-9634-1.CH006;TINTO V, 2017, J COLL STUD RETENT-R, V19, P254, DOI 10.1177/1521025115621917;TORRE M.E., 2009, URBAN REV, V41, P106, DOI DOI 10.1007/S11256-008-0097-7;UMBACH PD, 2005, RES HIGH EDUC, V46, P153, DOI 10.1007/S11162-004-1598-1;VILLALPANDO O., 2004, NEW DIRECTIONS FOR STUDENT SERVICES, P41, DOI DOI 10.1002/SS.115;WILSON D, 2015, RES HIGH EDUC, V56, P750, DOI 10.1007/S11162-015-9367-X;WON S, 2018, J EXP EDUC, V86, P402, DOI 10.1080/00220973.2016.1277337;YOSSO TJ, 2017, CRITICAL RACE THEORY IN EDUCATION: ALL GOD'S CHILDREN GOT A SONG, 2ND EDITION, P113;ZUMBRUNN S, 2014, INSTR SCI, V42, P661, DOI 10.1007/S11251-014-9310-0
## AB
## MOREAU CS, 2022, PATHOG DIS RACISM AND BIAS ARE PERVASIVE IN SOCIETY-AND SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) FIELDS ARE NOT IMMUNE TO THESE ISSUES. IT IS IMPERATIVE THAT WE EDUCATE OURSELVES AND OUR STUDENTS ABOUT THE HISTORY AND CONSEQUENCES OF THIS BIAS IN STEM, INVESTIGATE THE RESEARCH SHOWING BIAS TOWARD MARGINALIZED GROUPS, UNDERSTAND HOW TO INTERPRET MISUSES OF SCIENCE IN PERPETUATING BIAS, AND IDENTIFY ADVANCES AND SOLUTIONS TO OVERCOME RACISM AND BIAS THROUGHOUT OUR PROFESSIONAL AND PERSONAL LIVES. HERE, WE PRESENT ONE MODEL FOR TEACHING A UNIVERSAL COURSE FOR PARTICIPANTS OF ALL PROFESSIONAL STAGES TO ADDRESS THESE ISSUES AND INITIATE SOLUTIONS. AS VERY FEW INSTITUTIONS REQUIRE STUDENTS TO ENROLL IN COURSES ON RACISM AND BIAS IN STEM OR EVEN OFFER SUCH COURSES, OUR CURRICULUM COULD BE USED AS A BLUEPRINT FOR IMPLEMENTATION ACROSS INSTITUTIONS. ULTIMATELY, INSTITUTIONS AND ACADEMIC DISCIPLINES CAN INCORPORATE THIS IMPORTANT MATERIAL WITH MORE REGION AND/OR DISCIPLINE SPECIFIC STUDIES OF BIAS. THE AUTHORS PRESENT ONE MODEL FOR TEACHING A UNIVERSAL COURSE FOR PARTICIPANTS OF ALL PROFESSIONAL STAGES TO ADDRESS RACISM, BIAS, AND EXCLUSION IN STEM, AND DISCUSS THE LITERATURE AROUND THESE ISSUES AND WHY IT IS IMPORTANT TO TEACH COURSES LIKE THESE.
## O'HARA RM, 2022, J CONSTR PSYCHOL AT THE MOST BASIC LEVEL OF HUMAN EXISTENCE IS THE NEED TO FEEL LIKE ONE BELONGS. SENSE OF BELONGING IS CORRELATED WITH A PERSON'S MOTIVATION, DRIVE, BEHAVIOR, AND IDENTITY. RESEARCH SUGGESTS INSTITUTIONS OF HIGHER EDUCATION DO MUCH TO FOSTER STUDENTS' SENSE OF BELONGING AND CREATE POSITIVE LEARNING ENVIRONMENTS IN WHICH FACULTY USE THEIR POTENTIAL TO INFLUENCE STUDENT LEARNING, MOTIVATION, AND BELONGING. THIS PAPER USES CRITICAL RACE THEORY (CRT) TO EXAMINE THE PROBLEMS OF STUDENT ATTRITION, LACK OF PERSISTENCE, AND LACK OF A SENSE OF BELONGING AMONG MARGINALIZED POPULATIONS UNDERGOING SCIENCE, TECHNOLOGY, ENGINEERING, MATHEMATICS (STEM) EDUCATION WITHIN U.S. INSTITUTIONS OF HIGHER EDUCATION. USING CONSTRUCTS AND TENETS OF CRT, THIS PAPER SPECIFICALLY EXPLORES HOW RACE AND RACISM IN POST-SECONDARY STEM EDUCATION EXACERBATE THE PROBLEM WHILE USING CONTEXTUAL FACTORS AS A GUIDE. RESEARCHERS AND PRACTITIONERS ALIKE CAN USE THIS CRITICAL ANALYSIS TO SUPPORT CURRENT AND FUTURE WORK IN UNDERSTANDING HOW EDUCATIONAL PROGRAMS ARE SOCIALLY CONSTRUCTED IN A WAY THAT HISTORICALLY EXCLUDES MARGINALIZED PERSONS.
## AR BP
## MOREAU CS, 2022, PATHOG DIS FTAC006 <NA>
## O'HARA RM, 2022, J CONSTR PSYCHOL <NA> 986
## C1
## MOREAU CS, 2022, PATHOG DIS CORNELL UNIV, DEPT ENTOMOL, ITHACA, NY 14853 USA.; CORNELL UNIV, DEPT ECOL & EVOLUTIONARY BIOL, ITHACA, NY 14853 USA.; UNIV CALIF SAN DIEGO, DIV BIOL SCI, SECT CELL & DEV BIOL, SAN DIEGO, CA 92093 USA.;
## O'HARA RM, 2022, J CONSTR PSYCHOL CLEMSON UNIV, DEPT EDUC & HUMAN DEV, 101 GANTT CR, CLEMSON, SC 29631 USA.;
## C3
## MOREAU CS, 2022, PATHOG DIS CORNELL UNIVERSITY; CORNELL UNIVERSITY; UNIVERSITY OF CALIFORNIA SYSTEM; UNIVERSITY OF CALIFORNIA SAN DIEGO
## O'HARA RM, 2022, J CONSTR PSYCHOL CLEMSON UNIVERSITY
## CA DA
## MOREAU CS, 2022, PATHOG DIS <NA> 2024-07-01
## O'HARA RM, 2022, J CONSTR PSYCHOL <NA> 2024-07-01
## DE
## MOREAU CS, 2022, PATHOG DIS RACISM; BIAS; STEM; SOLUTIONS; DIALOGUE; INCLUSIVE PEDAGOGY; DIVERSITY; EQUITY; INCLUSION
## O'HARA RM, 2022, J CONSTR PSYCHOL <NA>
## DI DT
## MOREAU CS, 2022, PATHOG DIS 10.1093/femspd/ftac006 ARTICLE
## O'HARA RM, 2022, J CONSTR PSYCHOL 10.1080/10720537.2020.1842825 ARTICLE
## EA EF EI
## MOREAU CS, 2022, PATHOG DIS <NA> <NA> <NA>
## O'HARA RM, 2022, J CONSTR PSYCHOL NOV 2020 <NA> 1521-0650
## EM EP ER
## MOREAU CS, 2022, PATHOG DIS CORRIE.MOREAU@CORNELL.EDU <NA>
## O'HARA RM, 2022, J CONSTR PSYCHOL RMOHARA@CLEMSON.EDU 998
## FU
## MOREAU CS, 2022, PATHOG DIS NATIONAL SCIENCE FOUNDATION [NSF DEB 1398620]; CORNELL SLOAN FOUNDATION SCHOLARSHIP; FORD FOUNDATION PREDOCTORAL FELLOWSHIP; CORNELL ACTIVE LEARNING INITIATIVE
## O'HARA RM, 2022, J CONSTR PSYCHOL <NA>
## FX
## MOREAU CS, 2022, PATHOG DIS WE ARE TREMENDOUSLY GRATEFUL TO THE PARTICIPANTS OF ENTOM 4040 FOR THEIR ACTIVE ENGAGEMENT AND FEEDBACK ON THE COURSE. WE THANK ALBERTO CORREA, JULIA DSHEMUCHADSE, DAVID ESPARZA, ASH HEIM, KELLY SCHMID, LILLIAN SENN, MICHELLE SMITH, AND KIRA TREIBERGS FOR READING EARLIER VERSIONS OF THIS MANUSCRIPT AND PROVIDING HELPFUL FEEDBACK. C.S.M. WAS FUNDED IN PART BY A GRANT FROM THE NATIONAL SCIENCE FOUNDATION (NSF DEB 1398620). A.-J.C.D. WAS FUNDED IN PART BY THE CORNELL SLOAN FOUNDATION SCHOLARSHIP. L.M.A.H. WAS FUNDED BY THE CORNELL ACTIVE LEARNING INITIATIVE. A.M.D. WAS FUNDED IN PART BY THE FORD FOUNDATION PREDOCTORAL FELLOWSHIP. CORNELL UNIVERSITY IS LOCATED ON THE TRADITIONAL HOMELANDS OF THE GAYOGOHO:NO (THE CAYUGA NATION). THE GAYOGOHO:NO ARE MEMBERS OF THE HAUDENOSAUNEE CONFEDERACY, AN ALLIANCE OF SIX SOVEREIGN NATIONS WITH A HISTORIC AND CONTEMPORARY PRESENCE ON THIS LAND.
## O'HARA RM, 2022, J CONSTR PSYCHOL <NA>
## GA
## MOREAU CS, 2022, PATHOG DIS 0W0CO
## O'HARA RM, 2022, J CONSTR PSYCHOL 3D3YQ
## ID IS
## MOREAU CS, 2022, PATHOG DIS SCIENCE; WOMEN; DIVERSITY; PLACE; RACE 1
## O'HARA RM, 2022, J CONSTR PSYCHOL STUDENTS; PERSISTENCE; ENGAGEMENT; SCIENCE 3
## J9 JI LA
## MOREAU CS, 2022, PATHOG DIS PATHOG DIS PATHOG. DIS. ENGLISH
## O'HARA RM, 2022, J CONSTR PSYCHOL J CONSTR PSYCHOL J. CONSTR. PSYCHOL. ENGLISH
## NR OA
## MOREAU CS, 2022, PATHOG DIS 56 GREEN PUBLISHED, HYBRID
## O'HARA RM, 2022, J CONSTR PSYCHOL 52 <NA>
## OI
## MOREAU CS, 2022, PATHOG DIS DEMERY, AMELIA-JULIETTE/0000-0003-0634-9767; DARBY, ANDREA/0000-0001-9620-0194; MOREAU, CORRIE/0000-0003-1139-5792; MEADERS, CLARA/0000-0002-4620-141X
## O'HARA RM, 2022, J CONSTR PSYCHOL O'HARA, ROBERT M/0000-0001-7004-0487
## PA
## MOREAU CS, 2022, PATHOG DIS GREAT CLARENDON ST, OXFORD OX2 6DP, ENGLAND
## O'HARA RM, 2022, J CONSTR PSYCHOL 530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA
## PD PG PI PM PT
## MOREAU CS, 2022, PATHOG DIS APR 29 8 OXFORD 35389476 J
## O'HARA RM, 2022, J CONSTR PSYCHOL JUL 26 13 PHILADELPHIA <NA> J
## PU PY
## MOREAU CS, 2022, PATHOG DIS OXFORD UNIV PRESS 2022
## O'HARA RM, 2022, J CONSTR PSYCHOL TAYLOR & FRANCIS INC 2022
## RI
## MOREAU CS, 2022, PATHOG DIS <NA>
## O'HARA RM, 2022, J CONSTR PSYCHOL O'HARA, ROBERT M/GXG-2569-2022
## RP
## MOREAU CS, 2022, PATHOG DIS MOREAU, CS (CORRESPONDING AUTHOR), CORNELL UNIV, 129 GARDEN AVE,3129 COMSTOCK HALL, ITHACA, NY 14853 USA.
## O'HARA RM, 2022, J CONSTR PSYCHOL O'HARA, RM (CORRESPONDING AUTHOR), CLEMSON UNIV, DEPT EDUC & HUMAN DEV, 101 GANTT CR, CLEMSON, SC 29631 USA.
## SC
## MOREAU CS, 2022, PATHOG DIS IMMUNOLOGY; INFECTIOUS DISEASES; MICROBIOLOGY
## O'HARA RM, 2022, J CONSTR PSYCHOL PSYCHOLOGY
## SI SN
## MOREAU CS, 2022, PATHOG DIS <NA> 2049-632X
## O'HARA RM, 2022, J CONSTR PSYCHOL <NA> 1072-0537
## SO SU TC
## MOREAU CS, 2022, PATHOG DIS PATHOGENS AND DISEASE <NA> 1
## O'HARA RM, 2022, J CONSTR PSYCHOL JOURNAL OF CONSTRUCTIVIST PSYCHOLOGY <NA> 8
## TI
## MOREAU CS, 2022, PATHOG DIS A FRAMEWORK FOR EDUCATING AND EMPOWERING STUDENTS BY TEACHING ABOUT HISTORY AND CONSEQUENCES OF BIAS IN STEM
## O'HARA RM, 2022, J CONSTR PSYCHOL STEM(ING) THE TIDE: A CRITICAL RACE THEORY ANALYSIS IN STEM EDUCATION<SUP>1</SUP>
## U1 U2 UT VL
## MOREAU CS, 2022, PATHOG DIS 1 10 WOS:000788706500003 80
## O'HARA RM, 2022, J CONSTR PSYCHOL 2 11 WOS:000588520400001 35
## WC
## MOREAU CS, 2022, PATHOG DIS IMMUNOLOGY; INFECTIOUS DISEASES; MICROBIOLOGY
## O'HARA RM, 2022, J CONSTR PSYCHOL PSYCHOLOGY, CLINICAL
## WE
## MOREAU CS, 2022, PATHOG DIS SCIENCE CITATION INDEX EXPANDED (SCI-EXPANDED)
## O'HARA RM, 2022, J CONSTR PSYCHOL SOCIAL SCIENCE CITATION INDEX (SSCI)
## Z9
## MOREAU CS, 2022, PATHOG DIS 2
## O'HARA RM, 2022, J CONSTR PSYCHOL 11
## C1raw
## MOREAU CS, 2022, PATHOG DIS [MOREAU, CORRIE S.; DARBY, ANDREA M.] CORNELL UNIV, DEPT ENTOMOL, ITHACA, NY 14853 USA. [MOREAU, CORRIE S.; DEMERY, AMELIA-JULIETTE C.; HERNANDEZ, LINA M. ARCILA] CORNELL UNIV, DEPT ECOL & EVOLUTIONARY BIOL, ITHACA, NY 14853 USA. [MEADERS, CLARA L.] UNIV CALIF SAN DIEGO, DIV BIOL SCI, SECT CELL & DEV BIOL, SAN DIEGO, CA 92093 USA.
## O'HARA RM, 2022, J CONSTR PSYCHOL [O'HARA, ROBERT M.] CLEMSON UNIV, DEPT EDUC & HUMAN DEV, 101 GANTT CR, CLEMSON, SC 29631 USA.
## DB
## MOREAU CS, 2022, PATHOG DIS ISI
## O'HARA RM, 2022, J CONSTR PSYCHOL ISI
## AU_UN
## MOREAU CS, 2022, PATHOG DIS CORNELL UNIVERSITY; CORNELL UNIVERSITY; UNIVERSITY OF CALIFORNIA SYSTEM; UNIVERSITY OF CALIFORNIA SAN DIEGO
## O'HARA RM, 2022, J CONSTR PSYCHOL CLEMSON UNIVERSITY
## AU1_UN AU_UN_NR
## MOREAU CS, 2022, PATHOG DIS CORNELL UNIV NA
## O'HARA RM, 2022, J CONSTR PSYCHOL CLEMSON UNIV NA
## SR_FULL
## MOREAU CS, 2022, PATHOG DIS MOREAU CS, 2022, PATHOG DIS
## O'HARA RM, 2022, J CONSTR PSYCHOL O'HARA RM, 2022, J CONSTR PSYCHOL
## SR
## MOREAU CS, 2022, PATHOG DIS MOREAU CS, 2022, PATHOG DIS
## O'HARA RM, 2022, J CONSTR PSYCHOL O'HARA RM, 2022, J CONSTR PSYCHOL
dim(M3_dup)
## [1] 351 61
head(M3_dup, n = 2)
## AU
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE EO
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS TC;MORTON K
## AF
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE, EBONY OMOTOLA
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS, TIA C.;MORTON, KARISMA
## CR
## MCGEE EO, 2020, EDUC RESEARCHER ADSERIAS RP, 2017, RACE ETHNIC EDUC-UK, V20, P315, DOI 10.1080/13613324.2016.1260233;ALEXANDER QR, 2016, J DIVERS HIGH EDUC, V9, P307, DOI 10.1037/A0039705;ALLEN A. 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## AB
## MCGEE EO, 2020, EDUC RESEARCHER THE RACIALIZED STRUCTURE OF STEM (SCIENCE, TECHNOLOGY, ENGINEERING, MATHEMATICS) HIGHER EDUCATION MAINTAINS GROSS INEQUITIES THAT ARE ILLUSTRATIVE OF STRUCTURAL RACISM, WHICH BOTH INFORMS AND IS REINFORCED BY DISCRIMINATORY BELIEFS, POLICIES, VALUES, AND DISTRIBUTION OF RESOURCES. THUS, AN EXAMINATION INTO STRUCTURAL RACISM IN STEM IS NEEDED TO EXPOSE THE MARGINALIZATION OF UNDERREPRESENTED GROUPS IN STEM AND TO IMPROVE UNDERSTANDING OF THE STEM POLICIES, PRACTICES, AND PROCEDURES THAT ALLOW THE FOUNDATION OF RACISM TO REMAIN INTACT. I ARGUE THAT, EVEN AT THE TOP OF THE EDUCATION HIERARCHY, BLACK STEM DOCTORATE STUDENTS AND PHD DEGREE HOLDERS CONSISTENTLY ENDURE THE RACIST RESIDUE OF HIGHER EDUCATION INSTITUTIONS AND STEM EMPLOYERS. THUS, THIS MANUSCRIPT ALSO DISCUSSES HOW UNIVERSITIES INSTITUTIONALIZE DIVERSITY MENTORING PROGRAMS DESIGNED MOSTLY TO FIX (READ "ASSIMILATE") UNDERREPRESENTED STUDENTS OF COLOR WHILE IGNORING OR MINIMIZING THE ROLE OF THE STEM DEPARTMENTS IN CREATING RACIALLY HOSTILE WORK AND EDUCATIONAL SPACES. I ARGUE THAT, WITHOUT A CRITICAL EXAMINATION OF THE STRUCTURAL RACISM OMNIPRESENT IN THE STEM, PROGRESS IN RACIALLY DIVERSIFYING STEM WILL CONTINUE AT A SNAIL'S PACE.
## MADKINS TC, 2021, CAN J SCI MATH TECHN IF WE ENVISION A FUTURE FOR BLACK YOUNG LEARNERS WHERE THEIR FULL HUMANITY IS HONOURED AND EDUCATORS FACILITATE RIGOROUS SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM) LEARNING EXPERIENCES THAT ARE JUSTICE-FOCUSED, WE MUST DISRUPT SYSTEMIC RACISM NOW. IN THIS ARTICLE WE DISCUSS HOW ANTI-BLACKNESS IS PERVASIVE IN SCIENCE AND MATHEMATICS EDUCATION, ESPECIALLY FOR YOUNG LEARNERS. WE ALSO ADDRESS WHY TEACHER EDUCATORS MUST DISRUPT ANTI-BLACK RACISM IN OUR WORK WITH ELEMENTARY TEACHER CANDIDATES AND IN OUR RESEARCH. WE ARGUE THAT TO DO THIS WORK AND DISRUPT ANTI-BLACKNESS, ELEMENTARY TEACHER EDUCATORS AND TEACHER CANDIDATES NEED POLITICAL CLARITY (BEAUBOEUF-LAFONTANT, 1999). POLITICAL CLARITY IS THE UNDERSTANDING OF HOW STRUCTURAL AND SCHOOL INEQUALITIES WORK TO (RE)PRODUCE DIFFERENTIAL LEARNING EXPERIENCES FOR MINORITIZED LEARNERS. WE OFFER SUGGESTIONS FOR HOW TEACHER EDUCATORS CAN FURTHER DEVELOP THEIR TEACHER CANDIDATES' POLITICAL CLARITY. DRAWING UPON OUR PRIOR RESEARCH, COURSE ASSIGNMENTS, AND EXPERIENCES AS BLACK WOMEN EDUCATORS AND TEACHER EDUCATORS, WE SHARE EXAMPLES OF HOW AN INDIVIDUAL'S POLITICAL CLARITY CAN BE DEVELOPED WITHIN SCIENCE AND MATHEMATICS METHODS COURSES. IN DOING SO, WE BUILD UPON PRIOR RESEARCH IN STEM TEACHER EDUCATION ON HOW TEACHERS COME TO SEE TEACHING AS A POLITICAL ACT AND ENGAGE IN THE HARD WORK OF EQUITY-FOCUSED STEM TEACHING.
## AR BP
## MCGEE EO, 2020, EDUC RESEARCHER <NA> 633
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA> 239
## C1
## MCGEE EO, 2020, EDUC RESEARCHER VANDERBILT UNIV, DIVERS & STEM EDUC, PEABODY COLL, PMB 230 GPC 230 APPLETON PL, NASHVILLE, TN 37203 USA.;
## MADKINS TC, 2021, CAN J SCI MATH TECHN UNIV TEXAS AUSTIN, COLL EDUC, 1912 SPEEDWAY,STOP D5500, AUSTIN, TX 78712 USA.; UNIV NORTH TEXAS, COLL EDUC, 1155 UNION CIRCLE, DENTON, TX 76203 USA.;
## C3
## MCGEE EO, 2020, EDUC RESEARCHER VANDERBILT UNIVERSITY; VANDERBILT UNIVERSITY PEABODY COLLEGE
## MADKINS TC, 2021, CAN J SCI MATH TECHN UNIVERSITY OF TEXAS SYSTEM; UNIVERSITY OF TEXAS AUSTIN; UNIVERSITY OF NORTH TEXAS SYSTEM; UNIVERSITY OF NORTH TEXAS DENTON
## CA DA
## MCGEE EO, 2020, EDUC RESEARCHER <NA> 2024-07-01
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA> 2024-07-01
## DE
## MCGEE EO, 2020, EDUC RESEARCHER CULTURAL ANALYSIS; DISPARITIES; DOCTORAL; ENGINEERING EDUCATION; ENTREPRENEURSHIP; HBCUS; HIGHER EDUCATION; MENTORING; MINORITIZED; RACE; STEM; STRUCTURAL RACISM; TECHNOLOGY
## MADKINS TC, 2021, CAN J SCI MATH TECHN ANTI-BLACKNESS; ANTI-RACIST TEACHING; EQUITY; POLITICAL CLARITY; ELEMENTARY STEM EDUCATION
## DI DT
## MCGEE EO, 2020, EDUC RESEARCHER 10.3102/0013189X20972718 ARTICLE
## MADKINS TC, 2021, CAN J SCI MATH TECHN 10.1007/s42330-021-00159-1 ARTICLE
## EA EF EI
## MCGEE EO, 2020, EDUC RESEARCHER <NA> <NA> 1935-102X
## MADKINS TC, 2021, CAN J SCI MATH TECHN AUG 2021 <NA> 1942-4051
## EM EP ER FU
## MCGEE EO, 2020, EDUC RESEARCHER EBONY.MCGEE@VANDERBILT.EDU 644 <NA>
## MADKINS TC, 2021, CAN J SCI MATH TECHN TMADKINS@AUSTIN.UTEXAS.EDU 256 <NA>
## FX GA
## MCGEE EO, 2020, EDUC RESEARCHER <NA> OZ1OY
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA> UI9TW
## ID
## MCGEE EO, 2020, EDUC RESEARCHER MATHEMATICS EDUCATION; COLOR; BLACK; RACE; SCIENCE; IDENTITY; STUDENTS; HEALTH; WOMEN; EXPERIENCES
## MADKINS TC, 2021, CAN J SCI MATH TECHN CRITICAL RACE THEORY; PEDAGOGY; STORIES; EQUITY; AGENCY
## IS J9
## MCGEE EO, 2020, EDUC RESEARCHER 9 EDUC RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN 2 CAN J SCI MATH TECHN
## JI
## MCGEE EO, 2020, EDUC RESEARCHER EDUC. RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN CAN. J. SCI. MATH. TECHNOL. EDUC.
## LA NR OA
## MCGEE EO, 2020, EDUC RESEARCHER ENGLISH 116 BRONZE
## MADKINS TC, 2021, CAN J SCI MATH TECHN ENGLISH 103 BRONZE
## OI
## MCGEE EO, 2020, EDUC RESEARCHER <NA>
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS, TIA/0000-0002-2555-9025; MORTON, KARISMA/0000-0003-1054-3554
## PA
## MCGEE EO, 2020, EDUC RESEARCHER 2455 TELLER RD, THOUSAND OAKS, CA 91320 USA
## MADKINS TC, 2021, CAN J SCI MATH TECHN ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
## PD PG PI PM PT
## MCGEE EO, 2020, EDUC RESEARCHER DEC 12 THOUSAND OAKS <NA> J
## MADKINS TC, 2021, CAN J SCI MATH TECHN JUN 18 NEW YORK 38624762 J
## PU PY
## MCGEE EO, 2020, EDUC RESEARCHER SAGE PUBLICATIONS INC 2020
## MADKINS TC, 2021, CAN J SCI MATH TECHN SPRINGER 2021
## RI
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE, EBONY OMOTOLA/F-1747-2016
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA>
## RP
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE, EO (CORRESPONDING AUTHOR), VANDERBILT UNIV, DIVERS & STEM EDUC, PEABODY COLL, PMB 230 GPC 230 APPLETON PL, NASHVILLE, TN 37203 USA.
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS, TC (CORRESPONDING AUTHOR), UNIV TEXAS AUSTIN, COLL EDUC, 1912 SPEEDWAY,STOP D5500, AUSTIN, TX 78712 USA.
## SC SI
## MCGEE EO, 2020, EDUC RESEARCHER EDUCATION & EDUCATIONAL RESEARCH <NA>
## MADKINS TC, 2021, CAN J SCI MATH TECHN EDUCATION & EDUCATIONAL RESEARCH SI
## SN
## MCGEE EO, 2020, EDUC RESEARCHER 0013-189X
## MADKINS TC, 2021, CAN J SCI MATH TECHN 1492-6156
## SO
## MCGEE EO, 2020, EDUC RESEARCHER EDUCATIONAL RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN CANADIAN JOURNAL OF SCIENCE MATHEMATICS AND TECHNOLOGY EDUCATION
## SU TC
## MCGEE EO, 2020, EDUC RESEARCHER <NA> 171
## MADKINS TC, 2021, CAN J SCI MATH TECHN <NA> 22
## TI
## MCGEE EO, 2020, EDUC RESEARCHER INTERROGATING STRUCTURAL RACISM IN STEM HIGHER EDUCATION
## MADKINS TC, 2021, CAN J SCI MATH TECHN DISRUPTING ANTI-BLACKNESS WITH YOUNG LEARNERS IN STEM: STRATEGIES FOR ELEMENTARY SCIENCE AND MATHEMATICS TEACHER EDUCATION
## U1 U2 UT VL
## MCGEE EO, 2020, EDUC RESEARCHER 26 80 WOS:000594705200001 49
## MADKINS TC, 2021, CAN J SCI MATH TECHN 1 4 WOS:000681587200001 21
## WC
## MCGEE EO, 2020, EDUC RESEARCHER EDUCATION & EDUCATIONAL RESEARCH
## MADKINS TC, 2021, CAN J SCI MATH TECHN EDUCATION, SCIENTIFIC DISCIPLINES
## WE
## MCGEE EO, 2020, EDUC RESEARCHER SOCIAL SCIENCE CITATION INDEX (SSCI)
## MADKINS TC, 2021, CAN J SCI MATH TECHN EMERGING SOURCES CITATION INDEX (ESCI)
## Z9
## MCGEE EO, 2020, EDUC RESEARCHER 239
## MADKINS TC, 2021, CAN J SCI MATH TECHN 27
## C1raw
## MCGEE EO, 2020, EDUC RESEARCHER [MCGEE, EBONY OMOTOLA] VANDERBILT UNIV, DIVERS & STEM EDUC, PEABODY COLL, PMB 230 GPC 230 APPLETON PL, NASHVILLE, TN 37203 USA.
## MADKINS TC, 2021, CAN J SCI MATH TECHN [MADKINS, TIA C.] UNIV TEXAS AUSTIN, COLL EDUC, 1912 SPEEDWAY,STOP D5500, AUSTIN, TX 78712 USA. [MORTON, KARISMA] UNIV NORTH TEXAS, COLL EDUC, 1155 UNION CIRCLE, DENTON, TX 76203 USA.
## DB
## MCGEE EO, 2020, EDUC RESEARCHER ISI
## MADKINS TC, 2021, CAN J SCI MATH TECHN ISI
## AU_UN
## MCGEE EO, 2020, EDUC RESEARCHER VANDERBILT UNIVERSITY; VANDERBILT UNIVERSITY PEABODY COLLEGE
## MADKINS TC, 2021, CAN J SCI MATH TECHN UNIVERSITY OF TEXAS SYSTEM; UNIVERSITY OF TEXAS AUSTIN; UNIVERSITY OF NORTH TEXAS SYSTEM; UNIVERSITY OF NORTH TEXAS DENTON
## AU1_UN AU_UN_NR
## MCGEE EO, 2020, EDUC RESEARCHER VANDERBILT UNIV NA
## MADKINS TC, 2021, CAN J SCI MATH TECHN UNIV TEXAS AUSTIN NA
## SR_FULL
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE EO, 2020, EDUC RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS TC, 2021, CAN J SCI MATH TECHN
## SR
## MCGEE EO, 2020, EDUC RESEARCHER MCGEE EO, 2020, EDUC RESEARCHER
## MADKINS TC, 2021, CAN J SCI MATH TECHN MADKINS TC, 2021, CAN J SCI MATH TECHN
Although bibliometrics is primarily used to understand productivity and the impact of specific contributions to a field, the field has expanded to inform useful insights in systematic analysis.
results1 <- biblioAnalysis(M1_dup)
summary(results1, k=20, pause=F, width=130)
##
##
## MAIN INFORMATION ABOUT DATA
##
## Timespan 2003 : 2023
## Sources (Journals, Books, etc) 104
## Documents 278
## Annual Growth Rate % 14.35
## Document Average Age 4.21
## Average citations per doc 16.21
## Average citations per year per doc 2.492
## References 12411
##
## DOCUMENT TYPES
## article 259
## article; early access 19
##
## DOCUMENT CONTENTS
## Keywords Plus (ID) 425
## Author's Keywords (DE) 736
##
## AUTHORS
## Authors 659
## Author Appearances 776
## Authors of single-authored docs 76
##
## AUTHORS COLLABORATION
## Single-authored docs 94
## Documents per Author 0.422
## Co-Authors per Doc 2.79
## International co-authorships % 6.835
##
##
## Annual Scientific Production
##
## Year Articles
## 2003 5
## 2005 2
## 2007 3
## 2009 2
## 2010 2
## 2011 2
## 2012 3
## 2013 7
## 2014 4
## 2015 2
## 2016 9
## 2017 11
## 2018 17
## 2019 17
## 2020 17
## 2021 39
## 2022 63
## 2023 73
##
## Annual Percentage Growth Rate 14.35
##
##
## Most Productive Authors
##
## Authors Articles Authors Articles Fractionalized
## 1 MCGEE EO 8 MCGEE EO 4.50
## 2 LEYVA LA 5 BAYECK RY 2.00
## 3 DANCY M 3 ESTEVES O 2.00
## 4 MARTIN DB 3 GOUVEA JS 2.00
## 5 MCNEILL RT 3 GUNCKEL KL 2.00
## 6 MILES ML 3 HAGERMAN MA 2.00
## 7 MORALES-DOYLE D 3 HAMLIN ML 2.00
## 8 SMITH KN 3 LENZE NR 2.00
## 9 WOFFORD AM 3 MAIDANSKY A 2.00
## 10 ANDERSON J 2 MARTIN DB 2.00
## 11 AZADINHO MPM 2 NKRUMAH T 2.00
## 12 BATES S 2 OLSZEWSKI-KUBILIUS P 2.00
## 13 BAYECK RY 2 SELDEN S 2.00
## 14 BLACKHORSE D 2 SHOTWELL M 2.00
## 15 BRADLEY JA 2 STAVROU SG 2.00
## 16 BROCKMAN AJ 2 STITZLEIN SM 2.00
## 17 BROWN AR 2 SUNASEE R 2.00
## 18 BRUBAKER L 2 TAGER MB 2.00
## 19 CAMPLAIN R 2 LEYVA LA 1.53
## 20 CASSIANI S 2 MENSAH FM 1.50
##
##
## Top manuscripts per citations
##
## Paper DOI TC TCperYear NTC
## 1 MCGEE EO, 2011, AM EDUC RES J 10.3102/0002831211423972 289 20.64 1.329
## 2 GUTIÉRREZ R, 2013, J RES MATH EDUC NA 267 22.25 3.622
## 3 MCGEE EO, 2016, AM EDUC RES J 10.3102/0002831216676572 193 21.44 4.237
## 4 CONSTANTINE MG, 2007, J COUNS PSYCHOL 10.1037/0022-0167.54.2.142 184 10.22 2.875
## 5 MCGEE EO, 2020, EDUC RESEARCHER 10.3102/0013189X20972718 171 34.20 4.961
## 6 JOHNSON A, 2011, J RES SCI TEACH 10.1002/tea.20411 146 10.43 0.671
## 7 LEONARDO Z, 2013, EQUITY EXCELL EDUC 10.1080/10665684.2013.750539 114 9.50 1.547
## 8 BREM SK, 2003, SCI EDUC 10.1002/sce.10105 104 4.73 2.140
## 9 MARTIN DB, 2013, J RES MATH EDUC NA 92 7.67 1.248
## 10 AVRAAMIDOU L, 2020, CULT STUD SCI EDUCAT 10.1007/s11422-019-09954-7 86 17.20 2.495
## 11 TATE SA, 2018, ETHICS EDUC 10.1080/17449642.2018.1428718 85 12.14 3.507
## 12 TATE SA, 2018, ETHICS EDUC-a 10.1080/17449642.2018.1428718 85 12.14 3.507
## 13 MENSAH FM, 2018, TEACH COLL REC NA 81 11.57 3.342
## 14 MCCOY DL, 2015, J DIVERS HIGH EDUC 10.1037/a0038676 79 7.90 1.188
## 15 COLE ER, 2017, J DIVERS HIGH EDUC 10.1037/dhe0000044 67 8.38 3.760
## 16 NEMOTO T, 2003, AIDS EDUC PREV 10.1521/aeap.15.1.5.7.23616 66 3.00 1.358
## 17 GILLBORN D, 2016, J EDUC POLICY 10.1080/02680939.2016.1139189 63 7.00 1.383
## 18 BROWN BA, 2016, J RES SCI TEACH 10.1002/tea.21249 59 6.56 1.295
## 19 SHETH MJ, 2019, SCI EDUC 10.1002/sce.21450 56 9.33 3.294
## 20 SHAH N, 2020, J TEACH EDUC 10.1177/0022487119900204 56 11.20 1.625
##
##
## Corresponding Author's Countries
##
## Country Articles Freq SCP MCP MCP_Ratio
## 1 USA 217 0.78058 213 4 0.0184
## 2 BRAZIL 12 0.04317 10 2 0.1667
## 3 CANADA 12 0.04317 11 1 0.0833
## 4 UNITED KINGDOM 11 0.03957 11 0 0.0000
## 5 CHINA 3 0.01079 3 0 0.0000
## 6 FRANCE 3 0.01079 2 1 0.3333
## 7 SOUTH AFRICA 3 0.01079 1 2 0.6667
## 8 AUSTRALIA 2 0.00719 1 1 0.5000
## 9 FINLAND 2 0.00719 0 2 1.0000
## 10 IRELAND 2 0.00719 1 1 0.5000
## 11 NEW ZEALAND 2 0.00719 2 0 0.0000
## 12 RUSSIA 2 0.00719 2 0 0.0000
## 13 SPAIN 2 0.00719 0 2 1.0000
## 14 COLOMBIA 1 0.00360 0 1 1.0000
## 15 CYPRUS 1 0.00360 1 0 0.0000
## 16 ISRAEL 1 0.00360 0 1 1.0000
## 17 NETHERLANDS 1 0.00360 1 0 0.0000
## 18 SWEDEN 1 0.00360 0 1 1.0000
##
##
## SCP: Single Country Publications
##
## MCP: Multiple Country Publications
##
##
## Total Citations per Country
##
## Country Total Citations Average Article Citations
## 1 USA 3751 17.29
## 2 UNITED KINGDOM 372 33.82
## 3 NETHERLANDS 86 86.00
## 4 CANADA 61 5.08
## 5 CYPRUS 54 54.00
## 6 IRELAND 32 16.00
## 7 BRAZIL 31 2.58
## 8 AUSTRALIA 25 12.50
## 9 FRANCE 25 8.33
## 10 SOUTH AFRICA 14 4.67
## 11 COLOMBIA 11 11.00
## 12 CHINA 10 3.33
## 13 ISRAEL 10 10.00
## 14 SPAIN 10 5.00
## 15 FINLAND 8 4.00
## 16 NEW ZEALAND 6 3.00
## 17 SWEDEN 1 1.00
## 18 RUSSIA 0 0.00
##
##
## Most Relevant Sources
##
## Sources Articles
## 1 CULTURAL STUDIES OF SCIENCE EDUCATION 18
## 2 RACE ETHNICITY AND EDUCATION 13
## 3 JOURNAL OF CHEMICAL EDUCATION 11
## 4 ACADEMIC MEDICINE 10
## 5 JOURNAL OF DIVERSITY IN HIGHER EDUCATION 10
## 6 JOURNAL OF WOMEN AND MINORITIES IN SCIENCE AND ENGINEERING 10
## 7 FRONTIERS IN EDUCATION 9
## 8 SCIENCE EDUCATION 9
## 9 TEACHERS COLLEGE RECORD 7
## 10 AMERICAN BIOLOGY TEACHER 6
## 11 CANADIAN JOURNAL OF SCIENCE MATHEMATICS AND TECHNOLOGY EDUCATION 6
## 12 CBE-LIFE SCIENCES EDUCATION 6
## 13 JOURNAL OF SCIENCE TEACHER EDUCATION 6
## 14 ACM TRANSACTIONS ON COMPUTING EDUCATION 5
## 15 EQUITY & EXCELLENCE IN EDUCATION 5
## 16 JOURNAL OF RESEARCH IN SCIENCE TEACHING 5
## 17 AMERICAN EDUCATIONAL RESEARCH JOURNAL 4
## 18 EDUCATION SCIENCES 4
## 19 INTERNATIONAL JOURNAL OF STEM EDUCATION 4
## 20 PERIFERIA 4
##
##
## Most Relevant Keywords
##
## Author Keywords (DE) Articles Keywords-Plus (ID) Articles
## 1 RACE 35 RACE 52
## 2 RACISM 35 STUDENTS 49
## 3 CRITICAL RACE THEORY 28 EDUCATION 43
## 4 EQUITY 26 EXPERIENCES 35
## 5 STEM 16 SCIENCE 35
## 6 DIVERSITY 14 WOMEN 27
## 7 INTERSECTIONALITY 12 COLOR 26
## 8 SCIENCE EDUCATION 12 GENDER 24
## 9 TEACHER EDUCATION 12 CRITICAL RACE THEORY 21
## 10 HIGHER EDUCATION 11 DIVERSITY 20
## 11 GENDER 9 IDENTITY 17
## 12 SOCIAL JUSTICE 9 MATHEMATICS 17
## 13 MATHEMATICS EDUCATION 8 EQUITY 13
## 14 CURRICULUM 7 RACISM 13
## 15 ENGINEERING 7 SCHOOL 13
## 16 MINORITIES IN CHEMISTRY 7 TEACHERS 13
## 17 QUALITATIVE RESEARCH 7 BLACK 12
## 18 STEM EDUCATION 7 KNOWLEDGE 12
## 19 EDUCATION 6 IMPACT 11
## 20 ORGANIC CHEMISTRY 6 PERSISTENCE 11
plot(x=results1, k=10, pause=F)
results2 <- biblioAnalysis(M2_dup)
summary(results2, k=20, pause=F, width=130)
##
##
## MAIN INFORMATION ABOUT DATA
##
## Timespan 2003 : 2023
## Sources (Journals, Books, etc) 77
## Documents 132
## Annual Growth Rate % 19.1
## Document Average Age 3.42
## Average citations per doc 16.06
## Average citations per year per doc 2.768
## References 6764
##
## DOCUMENT TYPES
## article 128
## article; early access 4
##
## DOCUMENT CONTENTS
## Keywords Plus (ID) 352
## Author's Keywords (DE) 353
##
## AUTHORS
## Authors 398
## Author Appearances 461
## Authors of single-authored docs 28
##
## AUTHORS COLLABORATION
## Single-authored docs 36
## Documents per Author 0.332
## Co-Authors per Doc 3.49
## International co-authorships % 6.818
##
##
## Annual Scientific Production
##
## Year Articles
## 2003 1
## 2007 2
## 2009 1
## 2012 1
## 2013 1
## 2014 2
## 2015 6
## 2016 1
## 2019 8
## 2020 13
## 2021 25
## 2022 38
## 2023 33
##
## Annual Percentage Growth Rate 19.1
##
##
## Most Productive Authors
##
## Authors Articles Authors Articles Fractionalized
## 1 ROGERS LO 4 BINGAMAN KA 2.0
## 2 BARBARIN O 3 FAHNERT B 2.0
## 3 CASSIDY J 3 HUNT JM 2.0
## 4 STERN JA 3 SALZANO FM 2.0
## 5 ALIMOHAMED MZ 2 SPENCER MB 2.0
## 6 ALVAREZ L 2 SUNASEE R 2.0
## 7 ANDERSON J 2 WEISBERG M 2.0
## 8 APPLEWHITE D 2 WELCH M 2.0
## 9 AVELAR PH 2 ROGERS LO 1.2
## 10 BARDIEN S 2 ALVAREZ L 1.0
## 11 BINGAMAN KA 2 BARBARIN O 1.0
## 12 DAWSON DN 2 CASSIDY J 1.0
## 13 DHANNOON BN 2 CAUSADIAS JM 1.0
## 14 DIALLO RN 2 CLOUGH PT 1.0
## 15 EL-KAMAH G 2 DANIELS J 1.0
## 16 FAHNERT B 2 DHANNOON BN 1.0
## 17 GAYE A 2 GILBERT SF 1.0
## 18 GRAHAM JR 2 GRIFFITH EEH 1.0
## 19 HAMZAH NA 2 HAMZAH NA 1.0
## 20 HEBL M 2 KASUN P 1.0
##
##
## Top manuscripts per citations
##
## Paper DOI TC TCperYear NTC
## 1 BRONDOLO E, 2009, J BEHAV MED 10.1007/s10865-008-9190-3 573 35.81 1.000
## 2 CONSTANTINE MG, 2007, J COUNS PSYCHOL 10.1037/0022-0167.54.2.142 184 10.22 1.968
## 3 PRATES MOR, 2020, NEURAL COMPUT APPL 10.1007/s00521-019-04144-6 102 20.40 4.929
## 4 PRATES MOR, 2020, NEURAL COMPUT APPL-a 10.1007/s00521-019-04144-6 102 20.40 4.929
## 5 DAVIES SW, 2021, PLOS BIOL 10.1371/journal.pbio.3001282 89 22.25 5.691
## 6 PHELPS EA, 2003, NEUROPSYCHOLOGIA 10.1016/S0028-3932(02)00150-1 76 3.45 1.000
## 7 ROGERS LO, 2021, HUM DEV 10.1159/000519630 59 14.75 3.772
## 8 VOLPE VV, 2019, TRANSL ISS PSYCH SCI 10.1037/tps0000205 45 7.50 2.034
## 9 VOLPE VV, 2019, TRANSL ISS PSYCH SCI-a 10.1037/tps0000205 45 7.50 2.034
## 10 STERN JA, 2022, ATTACH HUM DEV 10.1080/14616734.2021.1976933 41 13.67 5.879
## 11 CASTRO-RAMIREZ F, 2021, J CLIN CHILD ADOLESC 10.1080/15374416.2021.1941058 40 10.00 2.558
## 12 WILLIAMS MT, 2019, NEW IDEAS PSYCHOL 10.1016/j.newideapsych.2019.05.002 39 6.50 1.763
## 13 DANIELS J, 2015, AM BEHAV SCI 10.1177/0002764215578728 37 3.70 3.964
## 14 DE WOLFE TJ, 2021, MSYSTEMS 10.1128/mSystems.00604-21 26 6.50 1.662
## 15 COOPER SM, 2022, CHILD DEV 10.1111/cdev.13783 23 7.67 3.298
## 16 GARRIOTT PO, 2019, J COUNS PSYCHOL 10.1037/cou0000351 22 3.67 0.994
## 17 MORALES-DOYLE D, 2021, COGNITION INSTRUCT 10.1080/07370008.2020.1828421 22 5.50 1.407
## 18 MATHUR SK, 2022, BEHAV ANAL PRACT 10.1007/s40617-021-00579-3 21 7.00 3.011
## 19 MOFFITT U, 2022, J RES ADOLESCENCE 10.1111/jora.12645 20 6.67 2.868
## 20 WILLIAMS TR, 2022, J PSYCHOTHER INTEGR 10.1037/int0000206 19 6.33 2.725
##
##
## Corresponding Author's Countries
##
## Country Articles Freq SCP MCP MCP_Ratio
## 1 USA 103 0.79231 99 4 0.0388
## 2 BRAZIL 4 0.03077 4 0 0.0000
## 3 UNITED KINGDOM 4 0.03077 2 2 0.5000
## 4 AUSTRALIA 3 0.02308 3 0 0.0000
## 5 CANADA 2 0.01538 1 1 0.5000
## 6 ETHIOPIA 2 0.01538 2 0 0.0000
## 7 IRAQ 2 0.01538 2 0 0.0000
## 8 SOUTH AFRICA 2 0.01538 0 2 1.0000
## 9 SWITZERLAND 2 0.01538 2 0 0.0000
## 10 COLOMBIA 1 0.00769 1 0 0.0000
## 11 DENMARK 1 0.00769 1 0 0.0000
## 12 ECUADOR 1 0.00769 1 0 0.0000
## 13 INDIA 1 0.00769 1 0 0.0000
## 14 NEW ZEALAND 1 0.00769 1 0 0.0000
## 15 TURKEY 1 0.00769 1 0 0.0000
##
##
## SCP: Single Country Publications
##
## MCP: Multiple Country Publications
##
##
## Total Citations per Country
##
## Country Total Citations Average Article Citations
## 1 USA 1816 17.631
## 2 BRAZIL 210 52.500
## 3 CANADA 31 15.500
## 4 UNITED KINGDOM 22 5.500
## 5 ETHIOPIA 14 7.000
## 6 TURKEY 9 9.000
## 7 SOUTH AFRICA 8 4.000
## 8 DENMARK 3 3.000
## 9 AUSTRALIA 2 0.667
## 10 NEW ZEALAND 2 2.000
## 11 INDIA 1 1.000
## 12 COLOMBIA 0 0.000
## 13 ECUADOR 0 0.000
## 14 IRAQ 0 0.000
## 15 SWITZERLAND 0 0.000
##
##
## Most Relevant Sources
##
## Sources Articles
## 1 JOURNAL OF CHEMICAL EDUCATION 11
## 2 JOURNAL OF ADOLESCENT RESEARCH 8
## 3 MOLECULAR BIOLOGY OF THE CELL 6
## 4 JOURNAL OF RESEARCH ON ADOLESCENCE 4
## 5 AMERICAN BEHAVIORAL SCIENTIST 3
## 6 ATTACHMENT & HUMAN DEVELOPMENT 3
## 7 COGNITION AND INSTRUCTION 3
## 8 JOURNAL OF BUSINESS AND PSYCHOLOGY 3
## 9 PASTORAL PSYCHOLOGY 3
## 10 TRANSLATIONAL ISSUES IN PSYCHOLOGICAL SCIENCE 3
## 11 APPLIED DEVELOPMENTAL SCIENCE 2
## 12 ARCHIVES OF SEXUAL BEHAVIOR 2
## 13 AUSTRALIAN COMMUNITY PSYCHOLOGIST 2
## 14 COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2
## 15 EGYPTIAN INFORMATICS JOURNAL 2
## 16 EVOLUTION & DEVELOPMENT 2
## 17 FAMILY PROCESS 2
## 18 FEMS MICROBIOLOGY LETTERS 2
## 19 HUMAN DEVELOPMENT 2
## 20 JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH 2
##
##
## Most Relevant Keywords
##
## Author Keywords (DE) Articles Keywords-Plus (ID) Articles
## 1 RACISM 24 RACE 18
## 2 RACE 16 DISCRIMINATION 13
## 3 ETHNICITY 11 EXPERIENCES 12
## 4 SOCIAL JUSTICE 8 RACISM 12
## 5 MINORITIES IN CHEMISTRY 7 SCIENCE 11
## 6 CRITICAL RACE THEORY 6 AFRICAN-AMERICAN 10
## 7 DIVERSITY 6 DIVERSITY 8
## 8 EQUITY 6 HEALTH 8
## 9 INCLUSION 6 IDENTITY 8
## 10 ORGANIC CHEMISTRY 6 STUDENTS 7
## 11 ADOLESCENCE 5 COLOR 6
## 12 COVID-19 5 GENDER 6
## 13 CURRICULUM 5 PSYCHOLOGY 6
## 14 DISCRIMINATION 5 RISK 6
## 15 SYSTEMIC RACISM 4 SOCIALIZATION 6
## 16 WHITENESS 4 WOMEN 6
## 17 WOMEN IN CHEMISTRY 4 YOUTH 6
## 18 ANTI-RACISM 3 CRITICAL RACE THEORY 5
## 19 ANTIRACISM 3 MENTAL-HEALTH 5
## 20 ATTACHMENT 3 MODEL 5
plot(x=results2, k=10, pause=F)
results3 <- biblioAnalysis(M3_dup)
summary(results3, k=20, pause=F, width=130)
##
##
## MAIN INFORMATION ABOUT DATA
##
## Timespan 2003 : 2023
## Sources (Journals, Books, etc) 181
## Documents 351
## Annual Growth Rate % 14.44
## Document Average Age 3.97
## Average citations per doc 17.39
## Average citations per year per doc 2.764
## References 18051
##
## DOCUMENT TYPES
## article 329
## article; early access 22
##
## DOCUMENT CONTENTS
## Keywords Plus (ID) 626
## Author's Keywords (DE) 1006
##
## AUTHORS
## Authors 1060
## Author Appearances 1119
## Authors of single-authored docs 106
##
## AUTHORS COLLABORATION
## Single-authored docs 109
## Documents per Author 0.331
## Co-Authors per Doc 3.19
## International co-authorships % 7.123
##
##
## Annual Scientific Production
##
## Year Articles
## 2003 6
## 2005 1
## 2007 3
## 2009 2
## 2010 2
## 2011 2
## 2012 4
## 2013 7
## 2014 5
## 2015 7
## 2016 9
## 2017 12
## 2018 14
## 2019 22
## 2020 26
## 2021 53
## 2022 87
## 2023 89
##
## Annual Percentage Growth Rate 14.44
##
##
## Most Productive Authors
##
## Authors Articles Authors Articles Fractionalized
## 1 MCGEE EO 8 MCGEE EO 4.50
## 2 LEYVA LA 5 MARTIN DB 2.00
## 3 MORALES-DOYLE D 4 NKRUMAH T 2.00
## 4 DANCY M 3 MORALES-DOYLE D 1.92
## 5 ERETE S 3 LEYVA LA 1.53
## 6 MARTIN DB 3 MENSAH FM 1.50
## 7 MCNEILL RT 3 SPARKS DM 1.50
## 8 MILES ML 3 ZEMBYLAS M 1.50
## 9 NISSEN J 3 RUSSO-TAIT T 1.33
## 10 ROGERS LO 3 NISSEN J 1.20
## 11 ATWATER MM 2 ABRICA EJ 1.00
## 12 BARBARIN O 2 AIKENHEAD GS 1.00
## 13 BROCKMAN AJ 2 AVRAAMIDOU L 1.00
## 14 CASSIDY J 2 BALDWIN-WHITE A 1.00
## 15 EL-HANI CN 2 BANAJI S 1.00
## 16 GALAMBA A 2 BANCROFT SF 1.00
## 17 GRAHAM JR 2 BAYECK RY 1.00
## 18 KING NS 2 BERY S 1.00
## 19 MADKINS TC 2 BICKFORD JH 1.00
## 20 MCGEE R 2 BINGAMAN KA 1.00
##
##
## Top manuscripts per citations
##
## Paper DOI TC TCperYear NTC
## 1 BRONDOLO E, 2009, J BEHAV MED 10.1007/s10865-008-9190-3 573 35.81 1.993
## 2 MCGEE EO, 2011, AM EDUC RES J 10.3102/0002831211423972 289 20.64 1.329
## 3 GUTIÉRREZ R, 2013, J RES MATH EDUC NA 267 22.25 3.580
## 4 MCGEE EO, 2016, AM EDUC RES J 10.3102/0002831216676572 193 21.44 4.237
## 5 CONSTANTINE MG, 2007, J COUNS PSYCHOL 10.1037/0022-0167.54.2.142 184 10.22 2.890
## 6 MCGEE EO, 2020, EDUC RESEARCHER 10.3102/0013189X20972718 171 34.20 5.671
## 7 JOHNSON A, 2011, J RES SCI TEACH 10.1002/tea.20411 146 10.43 0.671
## 8 MORALES-DOYLE D, 2017, SCI EDUC 10.1002/sce.21305 125 15.62 4.673
## 9 LEONARDO Z, 2013, EQUITY EXCELL EDUC 10.1080/10665684.2013.750539 114 9.50 1.529
## 10 BREM SK, 2003, SCI EDUC 10.1002/sce.10105 104 4.73 1.868
## 11 PRATES MOR, 2020, NEURAL COMPUT APPL 10.1007/s00521-019-04144-6 102 20.40 3.383
## 12 MARTIN DB, 2013, J RES MATH EDUC NA 92 7.67 1.234
## 13 DAVIES SW, 2021, PLOS BIOL 10.1371/journal.pbio.3001282 89 22.25 6.561
## 14 AVRAAMIDOU L, 2020, CULT STUD SCI EDUCAT 10.1007/s11422-019-09954-7 86 17.20 2.852
## 15 TATE SA, 2018, ETHICS EDUC 10.1080/17449642.2018.1428718 85 12.14 3.662
## 16 MENSAH FM, 2018, TEACH COLL REC NA 81 11.57 3.489
## 17 MCCOY DL, 2015, J DIVERS HIGH EDUC 10.1037/a0038676 79 7.90 2.973
## 18 PHELPS EA, 2003, NEUROPSYCHOLOGIA 10.1016/S0028-3932(02)00150-1 76 3.45 1.365
## 19 COLE ER, 2017, J DIVERS HIGH EDUC 10.1037/dhe0000044 67 8.38 2.505
## 20 NEMOTO T, 2003, AIDS EDUC PREV 10.1521/aeap.15.1.5.7.23616 66 3.00 1.186
##
##
## Corresponding Author's Countries
##
## Country Articles Freq SCP MCP MCP_Ratio
## 1 USA 275 0.78571 268 7 0.0255
## 2 UNITED KINGDOM 14 0.04000 12 2 0.1429
## 3 CANADA 13 0.03714 11 2 0.1538
## 4 BRAZIL 10 0.02857 8 2 0.2000
## 5 AUSTRALIA 5 0.01429 4 1 0.2000
## 6 NEW ZEALAND 4 0.01143 4 0 0.0000
## 7 SOUTH AFRICA 4 0.01143 2 2 0.5000
## 8 CHINA 3 0.00857 3 0 0.0000
## 9 COLOMBIA 2 0.00571 1 1 0.5000
## 10 FRANCE 2 0.00571 1 1 0.5000
## 11 IRELAND 2 0.00571 1 1 0.5000
## 12 SPAIN 2 0.00571 0 2 1.0000
## 13 CYPRUS 1 0.00286 1 0 0.0000
## 14 DENMARK 1 0.00286 1 0 0.0000
## 15 ECUADOR 1 0.00286 1 0 0.0000
## 16 ETHIOPIA 1 0.00286 1 0 0.0000
## 17 FINLAND 1 0.00286 0 1 1.0000
## 18 INDIA 1 0.00286 1 0 0.0000
## 19 IRAQ 1 0.00286 1 0 0.0000
## 20 ISRAEL 1 0.00286 0 1 1.0000
##
##
## SCP: Single Country Publications
##
## MCP: Multiple Country Publications
##
##
## Total Citations per Country
##
## Country Total Citations Average Article Citations
## 1 USA 5254 19.11
## 2 UNITED KINGDOM 309 22.07
## 3 BRAZIL 135 13.50
## 4 CANADA 91 7.00
## 5 NETHERLANDS 86 86.00
## 6 CYPRUS 54 54.00
## 7 IRELAND 32 16.00
## 8 AUSTRALIA 27 5.40
## 9 FRANCE 23 11.50
## 10 SOUTH AFRICA 16 4.00
## 11 COLOMBIA 11 5.50
## 12 CHINA 10 3.33
## 13 ISRAEL 10 10.00
## 14 NEW ZEALAND 10 2.50
## 15 SPAIN 10 5.00
## 16 TURKEY 9 9.00
## 17 ETHIOPIA 7 7.00
## 18 FINLAND 4 4.00
## 19 DENMARK 3 3.00
## 20 INDIA 1 1.00
##
##
## Most Relevant Sources
##
## Sources Articles
## 1 CULTURAL STUDIES OF SCIENCE EDUCATION 15
## 2 RACE ETHNICITY AND EDUCATION 12
## 3 JOURNAL OF DIVERSITY IN HIGHER EDUCATION 10
## 4 SCIENCE EDUCATION 10
## 5 JOURNAL OF CHEMICAL EDUCATION 9
## 6 ACADEMIC MEDICINE 8
## 7 JOURNAL OF WOMEN AND MINORITIES IN SCIENCE AND ENGINEERING 8
## 8 FRONTIERS IN EDUCATION 7
## 9 TEACHERS COLLEGE RECORD 7
## 10 CBE-LIFE SCIENCES EDUCATION 6
## 11 JOURNAL OF RESEARCH IN SCIENCE TEACHING 6
## 12 JOURNAL OF SCIENCE TEACHER EDUCATION 6
## 13 ACM TRANSACTIONS ON COMPUTING EDUCATION 5
## 14 CANADIAN JOURNAL OF SCIENCE MATHEMATICS AND TECHNOLOGY EDUCATION 5
## 15 EQUITY & EXCELLENCE IN EDUCATION 5
## 16 JOURNAL OF ADOLESCENT RESEARCH 5
## 17 AMERICAN BIOLOGY TEACHER 4
## 18 AMERICAN EDUCATIONAL RESEARCH JOURNAL 4
## 19 INTERNATIONAL JOURNAL OF STEM EDUCATION 4
## 20 JOURNAL OF RESEARCH ON ADOLESCENCE 4
##
##
## Most Relevant Keywords
##
## Author Keywords (DE) Articles Keywords-Plus (ID) Articles
## 1 RACISM 54 RACE 72
## 2 RACE 48 STUDENTS 53
## 3 CRITICAL RACE THEORY 33 EDUCATION 48
## 4 EQUITY 25 SCIENCE 44
## 5 STEM 18 EXPERIENCES 43
## 6 DIVERSITY 16 WOMEN 32
## 7 SOCIAL JUSTICE 15 COLOR 30
## 8 HIGHER EDUCATION 14 GENDER 29
## 9 INTERSECTIONALITY 13 DIVERSITY 26
## 10 ETHNICITY 11 CRITICAL RACE THEORY 25
## 11 SCIENCE EDUCATION 11 IDENTITY 24
## 12 TEACHER EDUCATION 10 RACISM 24
## 13 DISCRIMINATION 9 AFRICAN-AMERICAN 18
## 14 EDUCATION 9 DISCRIMINATION 17
## 15 GENDER 9 MATHEMATICS 17
## 16 QUALITATIVE RESEARCH 9 BLACK 15
## 17 COVID-19 8 EQUITY 14
## 18 SYSTEMIC RACISM 8 HEALTH 14
## 19 WHITENESS 8 SCHOOL 14
## 20 ANTI-RACISM 7 KNOWLEDGE 13
plot(x=results3, k=10, pause=F)
Results across the two samples indicate that the two disciplinary structures pull from very different sources of literature. The source of literature in the education sciences is highly concentrated whereas the literature in the STEM fields is more distributed.
Kimberlee Crenshaw’s 1993 Stanford Law Review article is the highest citation that shows up on both lists.
Researchers publishing in STEM outlets tend to not cite studies from education research. Studiens in education reserach, similarly, tend to pull from other studies in education.
CR1 <- citations(M1_dup, field = "article", sep = ";")
cbind(CR1$Cited[1:20])
## [,1]
## LADSONBILLINGS G, 1995, TEACH COLL REC, V97, P47 34
## FREIRE P., 2000, PEDAGOGY OF THE OPPRESSED 21
## MARTIN DB, 2009, TEACH COLL REC, V111, P295 20
## CARLONE HB, 2007, J RES SCI TEACH, V44, P1187, DOI 10.1002/TEA.20237 19
## DELGADO R., 2012, CRITICAL RACE THEORY 19
## SOLÓRZANO D, 2000, J NEGRO EDUC, V69, P60 19
## CRENSHAW K, 1993, STANFORD LAW REVIEW VOL 43, NO 6, JULY 1991, P1241 18
## MCGEE EO, 2016, AM EDUC RES J, V53, P1626, DOI 10.3102/0002831216676572 18
## MCGEE EO, 2017, COGNITION INSTRUCT, V35, P265, DOI 10.1080/07370008.2017.1355211 17
## MILNER IV H. R., 2007, EDUCATIONAL RESEARCHER, V36, P388, DOI DOI 10.3102/0013189X07309471, 10.3102/0013189X07309471 17
## YOSSO TJ, 2017, CRITICAL RACE THEORY IN EDUCATION: ALL GOD'S CHILDREN GOT A SONG, 2ND EDITION, P113 17
## BONILLA-SILVA EDUARDO, 2006, RACISM WITHOUT RACISTS: COLOR-BLIND RACISM AND THE PERSISTENCE OF RACIAL INEQUALITY IN THE UNITED STATES, V2ND, DOI DOI 10.5860/CHOICE.51.09.1531D 16
## LADSONBILLINGS G, 1995, AM EDUC RES J, V32, P465, DOI 10.3102/00028312032003465 16
## MCGEE EO, 2011, AM EDUC RES J, V48, P1347, DOI 10.3102/0002831211423972 16
## ONG M, 2011, HARVARD EDUC REV, V81, P172, DOI 10.17763/HAER.81.2.T022245N7X4752V2 16
## KENDI IBRAM X., 2019, BE ANTIRACIST 15
## SALDAA J., 2009, THE CODING MANUAL FOR QUALITATIVE RESEARCHERS, DOI DOI 10.1017/CBO9781107415324.004 15
## SUE DW, 2007, AM PSYCHOL, V62, P271, DOI 10.1037/0003-066X.62.4.271 15
## ONG M, 2018, J RES SCI TEACH, V55, P206, DOI 10.1002/TEA.21417 14
## SOLORZANO DANIEL G., 2002, QUALITATIVE INQUIRY, V8, P23 14
CR2 <- citations(M2_dup, field = "article", sep = ";")
cbind(CR2$Cited[1:20])
## [,1]
## CLARK R, 1999, AM PSYCHOL, V54, P805, DOI 10.1037/0003-066X.54.10.805 9
## HARRELL SP, 2000, AM J ORTHOPSYCHIAT, V70, P42, DOI 10.1037/H0087722 9
## KENDI IBRAM X., 2019, BE ANTIRACIST 9
## ROBERTS SO, 2020, PERSPECT PSYCHOL SCI, V15, P1295, DOI 10.1177/1745691620927709 9
## STEELE CM, 1997, AM PSYCHOL, V52, P613, DOI 10.1037/0003-066X.52.6.613 9
## BONILLA-SILVA EDUARDO, 2006, RACISM WITHOUT RACISTS: COLOR-BLIND RACISM AND THE PERSISTENCE OF RACIAL INEQUALITY IN THE UNITED STATES, V2ND, DOI DOI 10.5860/CHOICE.51.09.1531D 8
## COLL CG, 1996, CHILD DEV, V67, P1891, DOI 10.2307/1131600 8
## CRENSHAW K, 1993, STANFORD LAW REVIEW VOL 43, NO 6, JULY 1991, P1241 8
## SMEDLEY A, 2005, AM PSYCHOL, V60, P16, DOI 10.1037/0003-066X.60.1.16 8
## SUE DW, 2007, AM PSYCHOL, V62, P271, DOI 10.1037/0003-066X.62.4.271 7
## UMAÑA-TAYLOR AJ, 2014, CHILD DEV, V85, P21, DOI 10.1111/CDEV.12196 7
## PARADIES Y, 2015, PLOS ONE, V10, DOI 10.1371/JOURNAL.PONE.0138511 6
## SEATON EK, 2018, AM PSYCHOL, V73, P768, DOI 10.1037/AMP0000315 6
## SOLORZANO DANIEL G., 2002, QUALITATIVE INQUIRY, V8, P23 6
## BAILEY ZD, 2017, LANCET, V389, P1453, DOI 10.1016/S0140-6736(17)30569-X 5
## BARBER PH, 2020, SCIENCE, V369, P1440, DOI 10.1126/SCIENCE.ABD7140 5
## BONILLASILVA E, 1997, AM SOCIOL REV, V62, P465, DOI 10.2307/2657316 5
## BUCKLEY P, 2020, J CHEM EDUC, V97, P1327, DOI 10.1021/ACS.JCHEMED.9B00669 5
## CARBADO DW, 2014, ANNU REV LAW SOC SCI, V10, P149, DOI 10.1146/ANNUREV-LAWSOCSCI-110413-030928 5
## CRENSHAW K., 1989, UNIV CHICAGO LEG FOR, V1989, P139, DOI DOI 10.4324/9780429500480-5 5
CR3 <- citations(M3_dup, field = "article", sep = ";")
cbind(CR3$Cited[1:20])
## [,1]
## LADSONBILLINGS G, 1995, TEACH COLL REC, V97, P47 35
## CRENSHAW K, 1993, STANFORD LAW REVIEW VOL 43, NO 6, JULY 1991, P1241 25
## BONILLA-SILVA EDUARDO, 2006, RACISM WITHOUT RACISTS: COLOR-BLIND RACISM AND THE PERSISTENCE OF RACIAL INEQUALITY IN THE UNITED STATES, V2ND, DOI DOI 10.5860/CHOICE.51.09.1531D 23
## DELGADO R., 2012, CRITICAL RACE THEORY 23
## SOLÓRZANO D, 2000, J NEGRO EDUC, V69, P60 22
## CARLONE HB, 2007, J RES SCI TEACH, V44, P1187, DOI 10.1002/TEA.20237 21
## KENDI IBRAM X., 2019, BE ANTIRACIST 21
## FREIRE P., 2000, PEDAGOGY OF THE OPPRESSED 20
## MARTIN DB, 2009, TEACH COLL REC, V111, P295 20
## SUE DW, 2007, AM PSYCHOL, V62, P271, DOI 10.1037/0003-066X.62.4.271 20
## MCGEE EO, 2017, COGNITION INSTRUCT, V35, P265, DOI 10.1080/07370008.2017.1355211 19
## SOLORZANO DANIEL G., 2002, QUALITATIVE INQUIRY, V8, P23 19
## YOSSO TJ, 2017, CRITICAL RACE THEORY IN EDUCATION: ALL GOD'S CHILDREN GOT A SONG, 2ND EDITION, P113 19
## MCGEE EO, 2016, AM EDUC RES J, V53, P1626, DOI 10.3102/0002831216676572 18
## MILNER IV H. R., 2007, EDUCATIONAL RESEARCHER, V36, P388, DOI DOI 10.3102/0013189X07309471, 10.3102/0013189X07309471 18
## ONG M, 2011, HARVARD EDUC REV, V81, P172, DOI 10.17763/HAER.81.2.T022245N7X4752V2 17
## MCGEE EO, 2011, AM EDUC RES J, V48, P1347, DOI 10.3102/0002831211423972 16
## SALDAA J., 2009, THE CODING MANUAL FOR QUALITATIVE RESEARCHERS, DOI DOI 10.1017/CBO9781107415324.004 16
## STEELE CM, 1997, AM PSYCHOL, V52, P613, DOI 10.1037/0003-066X.52.6.613 16
## LADSONBILLINGS G, 1995, AM EDUC RES J, V32, P465, DOI 10.3102/00028312032003465 15
\[e = { Zp(1-p) \over \sqrt{n} }\]
NetMatrix1 <- biblioNetwork(M1_dup, analysis = "co-citation", network = "references", sep = ";")
net1=networkPlot(NetMatrix1, n = 50, Title = "Co-Citation Network", type = "fruchterman", size.cex=TRUE, size=20, remove.multiple=T, labelsize=1,edgesize = 10, edges.min=5)
NetMatrix2 <- biblioNetwork(M2_dup, analysis = "co-citation", network = "references", sep = ";")
net2=networkPlot(NetMatrix2, n = 50, Title = "Co-Citation Network", type = "fruchterman", size.cex=TRUE, size=20, remove.multiple=T, labelsize=1,edgesize = 10, edges.min=5)
NetMatrix3 <- biblioNetwork(M3_dup, analysis = "co-citation", network = "references", sep = ";")
net3=networkPlot(NetMatrix3, n = 50, Title = "Co-Citation Network", type = "fruchterman", size.cex=TRUE, size=20, remove.multiple=T, labelsize=1,edgesize = 10, edges.min=5)
netstat1 <- networkStat(NetMatrix1)
summary(netstat1,k=20)
##
##
## Main statistics about the network
##
## Size 12358
## Density 0.008
## Transitivity 0.538
## Diameter 6
## Degree Centralization 0.182
## Average path length 2.841
##
netstat2 <- networkStat(NetMatrix2)
summary(netstat2,k=20)
##
##
## Main statistics about the network
##
## Size 6730
## Density 0.015
## Transitivity 0.85
## Diameter 7
## Degree Centralization 0.109
## Average path length 3.227
##
netstat3 <- networkStat(NetMatrix3)
summary(netstat3,k=20)
##
##
## Main statistics about the network
##
## Size 17969
## Density 0.005
## Transitivity 0.576
## Diameter 6
## Degree Centralization 0.138
## Average path length 2.945
##
M1_dup=metaTagExtraction(M1_dup,"CR_SO",sep=";")
NetMatrix1 <- biblioNetwork(M1_dup, analysis = "co-citation", network = "sources", sep = ";")
net1 = networkPlot(NetMatrix1, n = 50, Title = "Co-Citation Network", type = "auto", size.cex=TRUE, size=15, remove.multiple=FALSE, labelsize=1,edgesize = 10, edges.min=5)
M2_dup=metaTagExtraction(M2_dup,"CR_SO",sep=";")
NetMatrix2 <- biblioNetwork(M2_dup, analysis = "co-citation", network = "sources", sep = ";")
net2 = networkPlot(NetMatrix2, n = 50, Title = "Co-Citation Network", type = "auto", size.cex=TRUE, size=15, remove.multiple=FALSE, labelsize=1,edgesize = 10, edges.min=5)
M3_dup=metaTagExtraction(M3_dup,"CR_SO",sep=";")
NetMatrix3 <- biblioNetwork(M3_dup, analysis = "co-citation", network = "sources", sep = ";")
net3 = networkPlot(NetMatrix3, n = 50, Title = "Co-Citation Network", type = "auto", size.cex=TRUE, size=15, remove.multiple=FALSE, labelsize=1,edgesize = 10, edges.min=5)
histResults1 <- histNetwork(M1_dup, sep = ";")
##
## WOS DB:
## Searching local citations (LCS) by reference items (SR) and DOIs...
##
## Analyzing 16244 reference items...
##
## Found 58 documents with no empty Local Citations (LCS)
options(width = 130)
net1 <- histPlot(histResults1, n=20, size = 5, labelsize = 4)
##
## Legend
##
## Label
## 1 MCGEE EO, 2011, AM EDUC RES J DOI 10.3102/0002831211423972
## 2 JOHNSON A, 2011, J RES SCI TEACH DOI 10.1002/TEA.20411
## 3 MCCOY DL, 2015, J DIVERS HIGH EDUC DOI 10.1037/A0038676
## 4 BROWN BA, 2016, J RES SCI TEACH DOI 10.1002/TEA.21249
## 5 MCGEE EO, 2016, AM EDUC RES J DOI 10.3102/0002831216676572
## 6 LARKIN DB, 2016, COGNITION INSTRUCT DOI 10.1080/07370008.2016.1215721
## 7 SPARKS DM, 2018, J SCI TEACH EDUC DOI 10.1080/1046560X.2018.1436359
## 8 PARSONS ERC, 2018, CULT STUD SCI EDUCAT DOI 10.1007/S11422-016-9774-0
## 9 SHETH MJ, 2019, SCI EDUC DOI 10.1002/SCE.21450
## 10 MENSAH FM, 2019, AM EDUC RES J DOI 10.3102/0002831218818093
## 11 MCGEE EO, 2020, EDUC RESEARCHER DOI 10.3102/0013189X20972718
## 12 LEE MGJ, 2020, INT J STEM EDUC DOI 10.1186/S40594-020-00241-4
## 13 SHAH N, 2020, J TEACH EDUC DOI 10.1177/0022487119900204
## 14 DANCY M, 2020, INT J STEM EDUC DOI 10.1186/S40594-020-00250-3
## 15 MADKINS TC, 2021, CAN J SCI MATH TECHN DOI 10.1007/S42330-021-00159-1
## 16 MORALES-DOYLE D, 2021, COGNITION INSTRUCT DOI 10.1080/07370008.2020.1828421
## 17 ALLEN D, 2022, INT J STEM EDUC DOI 10.1186/S40594-022-00334-2
## 18 MCNEILL RT, 2022, J LEARN SCI DOI 10.1080/10508406.2022.2073233
## 19 RUSSO-TAIT T, 2022, J RES SCI TEACH DOI 10.1002/TEA.21775
## 20 MORTON TR, 2022, J SCI TEACH EDUC DOI 10.1080/1046560X.2021.2008096
## 21 KING GP, 2023, CBE-LIFE SCI EDUC DOI 10.1187/CBE.22-06-0104
## Author_Keywords
## 1 RACIAL STEREOTYPES; IDENTITY; MATHEMATICS AND ENGINEERING EDUCATION; BLACK STUDENTS; HIGHER EDUCATION; HIGH ACHIEVEMENT
## 2 DIVERSITY; EQUITY; FEMINISM; GENDER/EQUITY; SOCIAL JUSTICE
## 3 COLORBLIND RACISM; MENTORING; STUDENTS OF COLOR
## 4 AFRICAN-AMERICAN; SCIENCE IDENTITY; MATRICULATION; ACCESS TO SCIENCE
## 5 STEREOTYPE MANAGEMENT; STEM STUDENTS OF COLOR; RACIAL HOSTILITY IN ACADEMIA; STEM RACIAL GAP; CULTURAL BIAS
## 6 <NA>
## 7 AFRICAN AMERICAN; FEMALE; FEMINISM; IDENTITY; INTERSECTIONALITY; STEM
## 8 SCIENCE EDUCATION; BLACK FACULTY; RACISM; HIGHER EDUCATION; CRITICAL RACE THEORY
## 9 CRITICAL RACE THEORY; EQUITY; PRACTICES; SCIENCE TEACHING; SECONDARY
## 10 CRITICAL RACE THEORY; TEACHER EDUCATION; TEACHERS OF COLOR; SCIENCE EDUCATION; INTERSECTIONALITY
## 11 CULTURAL ANALYSIS; DISPARITIES; DOCTORAL; ENGINEERING EDUCATION; ENTREPRENEURSHIP; HBCUS; HIGHER EDUCATION; MENTORING; MINORITIZED; RACE; STEM; STRUCTURAL RACISM; TECHNOLOGY
## 12 RACIAL MICROAGGRESSIONS; HIGHER EDUCATION; STEM; EDUCATIONAL SETTING; DIVERSITY CONCERNS
## 13 RACE; PRESERVICE TEACHER EDUCATION; TEACHER NOTICING; EQUITY
## 14 RACE; GENDER; UNDERGRADUATES; QUALITATIVE RESEARCH
## 15 ANTI-BLACKNESS; ANTI-RACIST TEACHING; EQUITY; POLITICAL CLARITY; ELEMENTARY STEM EDUCATION
## 16 <NA>
## 17 BLACK; MINORITY; WOMEN; STEM; COMMUNITY COLLEGE; TRANSFER; RACISM; SEXISM
## 18 <NA>
## 19 COLLEGE SCIENCE FACULTY; COLOR-BLIND RACISM; CRITICAL RACIAL CONSCIOUSNESS; RACIALLY MINORITIZED STUDENTS
## 20 BLACK STUDENTS; K-12 SCIENCE TEACHING; TEACHER EDUCATION; LIBERATION; ANTI-BLACKNESS
## 21 <NA>
## KeywordsPlus
## 1 CRITICAL RACE THEORY; AFRICAN-AMERICAN; RACIAL MICROAGGRESSIONS; TEST-PERFORMANCE; THREAT; IDENTITY; ACHIEVEMENT; EDUCATION; COLLEGE; GENDER
## 2 DISCURSIVE IDENTITY; FRAMEWORK; STUDENTS; PHYSICS; PARTICIPATION; CONSTRUCTION; EXPERIENCES; DISCOURSE; EDUCATION; LITERACY
## 3 COLLEGE-STUDENTS; AFRICAN-AMERICAN; GENDER; RACE; PERCEPTIONS; EXPERIENCES; WOMEN
## 4 EXPERIENCES; PERSISTENCE; STUDENTS
## 5 CRITICAL RACE THEORY; STEREOTYPE THREAT; SCIENCE; EXPERIENCES; EDUCATION; MICROAGGRESSIONS; MATHEMATICS; DIVERSITY; STUDENTS; COLOR
## 6 EDUCATING PROSPECTIVE TEACHERS; INQUIRY; BIOLOGY; RACISM; CONCEPTIONS; KNOWLEDGE; IDEOLOGY; IDENTITY; POVERTY; DESIGN
## 7 RACE; GENDER; WOMEN; STUDENTS; COLOR; COMMUNITY; MOVEMENT
## 8 CAMPUS RACIAL CLIMATE; AFRICAN-AMERICANS; FACULTY; MICROAGGRESSIONS; SATISFACTION; EDUCATION; COLLEGES; WORKLIFE
## 9 CRITICAL RACE THEORY; AMERICAN STUDENTS; MINORITY-STUDENTS; EDUCATION; EQUITY; MATHEMATICS; DIVERSITY; PERSPECTIVES; ACHIEVEMENT; PERSISTENCE
## 10 COLOR; PRESERVICE; WHITENESS; STUDENTS; MATHEMATICS; EXPERIENCES; IDENTITY; POLICIES
## 11 MATHEMATICS EDUCATION; COLOR; BLACK; RACE; SCIENCE; IDENTITY; STUDENTS; HEALTH; WOMEN; EXPERIENCES
## 12 AFRICAN-AMERICAN STUDENTS; CRITICAL RACE THEORY; PREDOMINANTLY WHITE; GENDER-DIFFERENCES; COLLEGE-STUDENTS; EXPERIENCES; CLIMATE; COLOR; STEREOTYPE; OPPORTUNITIES
## 13 RACIAL IDENTITY; DIVERSITY; PARTICIPATION; ATTITUDES; IDEOLOGY; COLOR; EDUCATION; CHILDREN; CULTURE; EQUITY
## 14 DOUBLE BIND; SCIENCE; WOMEN; RACE
## 15 CRITICAL RACE THEORY; PEDAGOGY; STORIES; EQUITY; AGENCY
## 16 CRITICAL RACE; AGENCY; CURRICULUM; EDUCATION; RELEVANCE; PEDAGOGY; STUDENTS; CRITIQUE
## 17 FEMALE TRANSFER STUDENTS; HIGHER-EDUCATION; TRANSFER SHOCK; ACADEMIC-PERFORMANCE; CHILLY CLIMATE; DOUBLE BIND; COLOR; GENDER; SCIENCE; UNDERGRADUATE
## 18 CRITICAL RACE THEORY; MATHEMATICS; PERSISTENCE; IDENTITIES; BLACK; OPPORTUNITIES; PERCEPTIONS; EXPERIENCES; EDUCATION; IDEOLOGY
## 19 STUDENTS; WOMEN; RACE; UNDERGRADUATE; EDUCATION; RACISM; GAPS; ACHIEVEMENT; PERFORMANCE; PERSISTENCE
## 20 RACE; STEM; EQUITY; CONSTRUCTION; MATHEMATICS; AMERICANS; PIPELINE; IDENTITY; STUDENTS; JUSTICE
## 21 HIGHER-EDUCATION; RACISM; COLOR; MATHEMATICS; STUDENTS; EXPERIENCES; IDEOLOGY; CLIMATE; WOMEN
## DOI Year LCS GCS
## 1 10.3102/0002831211423972 2011 16 289
## 2 10.1002/tea.20411 2011 4 146
## 3 10.1037/a0038676 2015 6 79
## 4 10.1002/tea.21249 2016 5 59
## 5 10.3102/0002831216676572 2016 18 193
## 6 10.1080/07370008.2016.1215721 2016 5 17
## 7 10.1080/1046560X.2018.1436359 2018 2 6
## 8 10.1007/s11422-016-9774-0 2018 2 9
## 9 10.1002/sce.21450 2019 13 56
## 10 10.3102/0002831218818093 2019 6 40
## 11 10.3102/0013189X20972718 2020 12 171
## 12 10.1186/s40594-020-00241-4 2020 3 54
## 13 10.1177/0022487119900204 2020 3 56
## 14 10.1186/s40594-020-00250-3 2020 2 18
## 15 10.1007/s42330-021-00159-1 2021 4 22
## 16 10.1080/07370008.2020.1828421 2021 3 22
## 17 10.1186/s40594-022-00334-2 2022 2 11
## 18 10.1080/10508406.2022.2073233 2022 2 4
## 19 10.1002/tea.21775 2022 2 11
## 20 10.1080/1046560X.2021.2008096 2022 2 16
## 21 10.1187/cbe.22-06-0104 2023 2 10
histResults2 <- histNetwork(M2_dup, sep = ";")
##
## WOS DB:
## Searching local citations (LCS) by reference items (SR) and DOIs...
##
## Analyzing 7973 reference items...
##
## Found 18 documents with no empty Local Citations (LCS)
options(width = 130)
net2 <- histPlot(histResults2, n=20, size = 5, labelsize = 4)
##
## Legend
##
## Label
## 1 BRONDOLO E, 2009, J BEHAV MED DOI 10.1007/S10865-008-9190-3
## 2 WEST LM, 2013, J CONTEXT BEHAV SCI DOI 10.1016/J.JCBS.2013.03.003
## 3 GRAHAM JR, 2015, J CONTEXT BEHAV SCI DOI 10.1016/J.JCBS.2014.11.001
## 4 LARKIN DB, 2016, COGNITION INSTRUCT DOI 10.1080/07370008.2016.1215721
## 5 BARBARIN OA, 2020, APPL DEV SCI DOI 10.1080/10888691.2019.1702880
## 6 CLARK GA, 2020, J CHEM EDUC DOI 10.1021/ACS.JCHEMED.9B00408
## 7 KORNBLUH M, 2021, J ADOLESCENT RES DOI 10.1177/07435584211031450
## 8 KORNBLUH M, 2021, J ADOLESCENT RES DOI 10.1177/07435584211031450
## 9 ROGERS LO, 2021, HUM DEV DOI 10.1159/000519630
## 10 ALDANA A, 2021, J ADOLESCENT RES DOI 10.1177/07435584211043289
## 11 FINE M, 2021, J ADOLESCENT RES DOI 10.1177/07435584211034873
## 12 MORALES-DOYLE D, 2021, COGNITION INSTRUCT DOI 10.1080/07370008.2020.1828421
## 13 SEATON EK, 2022, J RES ADOLESCENCE DOI 10.1111/JORA.12783
## 14 MOFFITT U, 2022, J RES ADOLESCENCE DOI 10.1111/JORA.12645
## 15 STERN JA, 2022, ATTACH HUM DEV DOI 10.1080/14616734.2021.1976933
## 16 HOLLOND C, 2022, J CHEM EDUC DOI 10.1021/ACS.JCHEMED.1C00382
## 17 PIERSON AM, 2022, COGN BEHAV PRACT DOI
## 18 COOPER SM, 2022, CHILD DEV DOI 10.1111/CDEV.13783
## 19 DUSEN B, 2022, J CHEM EDUC DOI 10.1021/ACS.JCHEMED.1C00352
## 20 BELIZAIRE S, 2023, FAM PROCESS DOI 10.1111/FAMP.12951
## 21 SUNASEE R, 2023, J CHEM EDUC DOI 10.1021/ACS.JCHEMED.3C00528
## 22 SUNASEE R, 2023, J CHEM EDUC DOI 10.1021/ACS.JCHEMED.3C00528
## 23 KING DD, 2023, J BUS PSYCHOL DOI 10.1007/S10869-022-09804-4
## 24 YU A, 2023, J CHEM EDUC DOI 10.1021/ACS.JCHEMED.2C00755
## 25 YU A, 2023, J CHEM EDUC DOI 10.1021/ACS.JCHEMED.2C00755
## 26 RUGGS EN, 2023, J BUS PSYCHOL DOI 10.1007/S10869-022-09855-7
## 27 RUGGS EN, 2023, J BUS PSYCHOL DOI 10.1007/S10869-022-09855-7
## 28 SATTERTHWAITE-FREIMAN M, 2023, HUM DEV DOI 10.1159/000534965
## 29 TORRES D, 2023, J CHEM EDUC DOI 10.1021/ACS.JCHEMED.3C00193
## Author_Keywords
## 1 ETHNICITY; HEALTH DISPARITIES; RACE; RACISM; HEALTH
## 2 BLACK AMERICAN; PERCEIVED RACIAL DISCRIMINATION; VALUES CLARIFICATION
## 3 RACISM; AFRICAN AMERICAN; ANXIETY; VALUES; DEPRESSION
## 4 <NA>
## 5 <NA>
## 6 FIRST-YEAR UNDERGRADUATE/GENERAL; BIOCHEMISTRY; ORGANIC CHEMISTRY; LABORATORY INSTRUCTION; HANDS-ON LEARNING/MANIPULATIVES; APPLICATIONS OF CHEMISTRY; CARBOHYDRATES; MINORITIES IN CHEMISTRY; NONMAJOR COURSES; CHEMICAL EDUCATION RESEARCH
## 7 SOCIAL JUSTICE; MIXED METHODS; QUALITATIVE METHODS; QUANTITATIVE METHODS; RACE; ETHNICITY; ADOLESCENCE
## 8 SOCIAL JUSTICE; MIXED METHODS; QUALITATIVE METHODS; QUANTITATIVE METHODS; RACE; ETHNICITY; ADOLESCENCE
## 9 RACISM; RESISTANCE; WHITE SUPREMACY; ANTI-BLACKNESS; ECOLOGICAL SYSTEMS THEORIES; RACIAL SOCIALIZATION; ANTI-RACISM SOCIALIZATION; INTERSECTIONALITY; BLACK LIVES MATTER
## 10 COMMUNITY-BASED PARTICIPATORY RESEARCH; RACE; ETHNICITY; SOCIAL JUSTICE; ADOLESCENCE
## 11 PARTICIPATORY ACTION RESEARCH; YOUTH ACTIVISM; RACIAL JUSTICE; PANDEMIC
## 12 <NA>
## 13 RACISM; WHITENESS; WHITE YOUTH
## 14 WHITE RACIAL IDENTITY; RACIAL IDENTITY DEVELOPMENT; WHITENESS; WHITE YOUTH; QUALITATIVE RESEARCH; EARLY ADOLESCENCE
## 15 ATTACHMENT; AFRICAN AMERICANS; BLACK YOUTH DEVELOPMENT; ANTI-RACISM
## 16 UPPER-DIVISION UNDERGRADUATE; BIOCHEMISTRY; CURRICULUM; INTERDISCIPLINARY/MULTIDISCIPLINARY; PUBLIC UNDERSTANDING/OUTREACH; COMMUNICATION/WRITING; PROBLEM SOLVING/DECISION MAKING; APPLICATIONS OF CHEMISTRY
## 17 ANTIRACISM; CULTURAL ADAPTATION; DBT; CRITICAL RACE THEORY
## 18 <NA>
## 19 GENERAL PUBLIC; TESTING/ASSESSMENT; WOMEN IN CHEMISTRY; MINORITIES IN CHEMISTRY; CHEMICAL EDUCATION RESEARCH
## 20 ANTIRACISM; CAREGIVERS; PARENTING; SOCIAL IDENTITY DEVELOPMENT; SYMBOLIC INTERACTIONISM; WHITENESS
## 21 SECOND-YEAR UNDERGRADUATE; ORGANIC CHEMISTRY; TESTING/ASSESSMENT; MINORITIES IN CHEMISTRY; INCLUSIVETEACHING; BROADENING PARTICIPATION; CULTURAL RELEVANCE
## 22 SECOND-YEAR UNDERGRADUATE; ORGANIC CHEMISTRY; TESTING/ASSESSMENT; MINORITIES IN CHEMISTRY; INCLUSIVETEACHING; BROADENING PARTICIPATION; CULTURAL RELEVANCE
## 23 ANTI-BLACK RACISM; ANTIRACISM; RACE; BLACK EMPLOYEES; CRITICAL RACE THEORY
## 24 INTRODUCTORY CHEMISTRY; ORGANIC CHEMISTRY; LAB EXERCISE; SOCIAL JUSTICE; WOMEN IN CHEMISTRY; DIVERSITY; EQUITY; INCLUSION; CURRICULUM
## 25 INTRODUCTORY CHEMISTRY; ORGANIC CHEMISTRY; LAB EXERCISE; SOCIAL JUSTICE; WOMEN IN CHEMISTRY; DIVERSITY; EQUITY; INCLUSION; CURRICULUM
## 26 <NA>
## 27 <NA>
## 28 <NA>
## 29 ORGANIC CHEMISTRY; MINORITIES IN CHEMISTRY; WOMEN IN CHEMISTRY; ANALOGIES; TRANSFER; COLLABORATIVE; COOPERATIVELEARNING; DISTANCE LEARNING; SELF INSTRUCTION
## KeywordsPlus
## 1 CARDIOVASCULAR REACTIVITY; AFRICAN-AMERICAN; PERCEIVED DISCRIMINATION; SOCIOECONOMIC-STATUS; BLOOD-PRESSURE; SUBSTANCE USE; STRESS; WOMEN; CARE; HYPERTENSION
## 2 BLOOD-PRESSURE; AFRICAN-AMERICANS; DISCRIMINATION; STRESSORS; RESPONSES; DISORDER; IDENTITY; ANXIETY; IMAGERY; RISK
## 3 GENERALIZED ANXIETY DISORDER; AFRICAN-AMERICAN; MENTAL-HEALTH; ETHNIC-DIFFERENCES; PERCEIVED RACIST; SEXIST EVENTS; DISCRIMINATION; IDENTITY; STRESS; ACCEPTANCE
## 4 EDUCATING PROSPECTIVE TEACHERS; INQUIRY; BIOLOGY; RACISM; CONCEPTIONS; KNOWLEDGE; IDEOLOGY; IDENTITY; POVERTY; DESIGN
## 5 COMMUNITY VIOLENCE; GENDER-DIFFERENCES; PERCEIVED DISCRIMINATION; RACIAL SOCIALIZATION; ACADEMIC-ACHIEVEMENT; SUBSTANCE USE; BLACK; EXPOSURE; YOUTH; RISK
## 6 QUALITATIVE TESTS; SOCIAL-JUSTICE; CHEMISTRY; URINE
## 7 <NA>
## 8 <NA>
## 9 ETHNIC-RACIAL SOCIALIZATION; SOCIAL CONSTRUCTION; RACE SOCIALIZATION; COLOR-BLINDNESS; IDENTITY; PSYCHOLOGY; PERSPECTIVE; MINORITY; STEREOTYPES; PRECURSORS
## 10 CIVIC ENGAGEMENT; CONSCIOUSNESS; PSYCHOLOGY; STUDENTS; RACE
## 11 PARTICIPATORY ACTION RESEARCH; COMMUNITY
## 12 CRITICAL RACE; AGENCY; CURRICULUM; EDUCATION; RELEVANCE; PEDAGOGY; STUDENTS; CRITIQUE
## 13 RACISM
## 14 RACE; DISCRIMINATION; ADOLESCENTS; SOCIALIZATION; CONSEQUENCES; MINORITY; CHILDREN; CONTEXT; BLACK; TALK
## 15 EARLY-CHILDHOOD ADVERSITY; RACISM-RELATED STRESS; AFRICAN-AMERICAN; METAANALYTIC EVIDENCE; LIFE-SPAN; EXPERIENCES; SENSITIVITY; SECURITY; CHILDREN; BEHAVIOR
## 16 MOTIVATION; CURRICULUM
## 17 CRITICAL RACE THEORY; CULTURAL COMPETENCE; AFRICAN-AMERICAN; HEALTH; HUMILITY
## 18 RACISM-RELATED STRESS; COLOR-BLIND; INITIAL VALIDATION; STRUCTURAL RACISM; SOCIALIZATION; YOUTH; DISCRIMINATION; DIVERSITY; ATTITUDES; FAMILIES
## 19 FEMALE STUDENTS; EQUITY; INSTRUCTION; ACHIEVEMENT; CONCEPTIONS; INVENTORY; VALIDITY; GENDER; MODEL; COLOR
## 20 RACIAL-ATTITUDES; SELF-REGULATION; COLOR-BLINDNESS; ATTACHMENT SECURITY; EMPATHY DEVELOPMENT; EXPLICIT PREJUDICE; PERSPECTIVE-TAKING; PROSOCIAL BEHAVIOR; INTERGROUP ANXIETY; PSYCHOSOCIAL COSTS
## 21 <NA>
## 22 <NA>
## 23 AFFIRMATIVE-ACTION PROGRAMS; CRITICAL RACE THEORY; AFRICAN-AMERICAN; RESEARCH PARTICIPATION; COLOR-BLINDNESS; ETHNIC DISPARITIES; STRUCTURAL RACISM; LEVEL DIVERSITY; LIFE EXPERIENCE; AVERSIVE RACISM
## 24 <NA>
## 25 <NA>
## 26 <NA>
## 27 <NA>
## 28 SOCIALIZATION; DISCRIMINATION; YOUTH; RACE; CONSTRUCTION; DIRECTIONS; IDEOLOGY; MINORITY; CULTURES; FUTURE
## 29 COLLEGE; GENDER; STEM; GAP; EXPERIENCES; CURRICULUM; SCIENCE; IMPACT
## DOI Year LCS GCS
## 1 10.1007/s10865-008-9190-3 2009 2 573
## 2 10.1016/j.jcbs.2013.03.003 2013 1 13
## 3 10.1016/j.jcbs.2014.11.001 2015 0 12
## 4 10.1080/07370008.2016.1215721 2016 1 17
## 5 10.1080/10888691.2019.1702880 2020 1 19
## 6 10.1021/acs.jchemed.9b00408 2020 1 12
## 7 10.1177/07435584211031450 2021 2 11
## 8 10.1177/07435584211031450 2021 2 11
## 9 10.1159/000519630 2021 3 59
## 10 10.1177/07435584211043289 2021 1 11
## 11 10.1177/07435584211034873 2021 3 9
## 12 10.1080/07370008.2020.1828421 2021 0 22
## 13 10.1111/jora.12783 2022 1 7
## 14 10.1111/jora.12645 2022 2 20
## 15 10.1080/14616734.2021.1976933 2022 0 41
## 16 10.1021/acs.jchemed.1c00382 2022 2 6
## 17 2022 0 6
## 18 10.1111/cdev.13783 2022 1 23
## 19 10.1021/acs.jchemed.1c00352 2022 1 19
## 20 10.1111/famp.12951 2023 0 1
## 21 10.1021/acs.jchemed.3c00528 2023 0 3
## 22 10.1021/acs.jchemed.3c00528 2023 0 3
## 23 10.1007/s10869-022-09804-4 2023 2 18
## 24 10.1021/acs.jchemed.2c00755 2023 2 2
## 25 10.1021/acs.jchemed.2c00755 2023 2 2
## 26 10.1007/s10869-022-09855-7 2023 0 3
## 27 10.1007/s10869-022-09855-7 2023 0 3
## 28 10.1159/000534965 2023 0 1
## 29 10.1021/acs.jchemed.3c00193 2023 0 1
histResults3 <- histNetwork(M3_dup, sep = ";")
##
## WOS DB:
## Searching local citations (LCS) by reference items (SR) and DOIs...
##
## Analyzing 22073 reference items...
##
## Found 73 documents with no empty Local Citations (LCS)
options(width = 130)
net3 <- histPlot(histResults3, n=20, size = 5, labelsize = 4)
##
## Legend
##
## Label
## 1 MCGEE EO, 2011, AM EDUC RES J DOI 10.3102/0002831211423972
## 2 JOHNSON A, 2011, J RES SCI TEACH DOI 10.1002/TEA.20411
## 3 MCCOY DL, 2015, J DIVERS HIGH EDUC DOI 10.1037/A0038676
## 4 BROWN BA, 2016, J RES SCI TEACH DOI 10.1002/TEA.21249
## 5 MCGEE EO, 2016, AM EDUC RES J DOI 10.3102/0002831216676572
## 6 LARKIN DB, 2016, COGNITION INSTRUCT DOI 10.1080/07370008.2016.1215721
## 7 MORALES-DOYLE D, 2017, SCI EDUC DOI 10.1002/SCE.21305
## 8 SPARKS DM, 2018, J SCI TEACH EDUC DOI 10.1080/1046560X.2018.1436359
## 9 PARSONS ERC, 2018, CULT STUD SCI EDUCAT DOI 10.1007/S11422-016-9774-0
## 10 MORALES-DOYLE D, 2019, RACE ETHNIC EDUC-UK DOI 10.1080/13613324.2019.1592840
## 11 SHETH MJ, 2019, SCI EDUC DOI 10.1002/SCE.21450
## 12 MENSAH FM, 2019, AM EDUC RES J DOI 10.3102/0002831218818093
## 13 MCGEE EO, 2020, EDUC RESEARCHER DOI 10.3102/0013189X20972718
## 14 LEE MGJ, 2020, INT J STEM EDUC DOI 10.1186/S40594-020-00241-4
## 15 SHAH N, 2020, J TEACH EDUC DOI 10.1177/0022487119900204
## 16 DANCY M, 2020, INT J STEM EDUC DOI 10.1186/S40594-020-00250-3
## 17 VAN DUSEN B, 2020, J RES SCI TEACH DOI 10.1002/TEA.21584
## 18 MADKINS TC, 2021, CAN J SCI MATH TECHN DOI 10.1007/S42330-021-00159-1
## 19 NISSEN JM, 2021, PHYS REV PHYS EDUC R DOI 10.1103/PHYSREVPHYSEDUCRES.17.010116
## 20 MORALES-DOYLE D, 2021, COGNITION INSTRUCT DOI 10.1080/07370008.2020.1828421
## 21 KORNBLUH M, 2021, J ADOLESCENT RES DOI 10.1177/07435584211031450
## 22 ROGERS LO, 2021, HUM DEV DOI 10.1159/000519630
## 23 FINE M, 2021, J ADOLESCENT RES DOI 10.1177/07435584211034873
## 24 ALLEN D, 2022, INT J STEM EDUC DOI 10.1186/S40594-022-00334-2
## 25 MCNEILL RT, 2022, J LEARN SCI DOI 10.1080/10508406.2022.2073233
## 26 RUSSO-TAIT T, 2022, J RES SCI TEACH DOI 10.1002/TEA.21775
## 27 MORTON TR, 2022, J SCI TEACH EDUC DOI 10.1080/1046560X.2021.2008096
## 28 KING GP, 2023, CBE-LIFE SCI EDUC DOI 10.1187/CBE.22-06-0104
## Author_Keywords
## 1 RACIAL STEREOTYPES; IDENTITY; MATHEMATICS AND ENGINEERING EDUCATION; BLACK STUDENTS; HIGHER EDUCATION; HIGH ACHIEVEMENT
## 2 DIVERSITY; EQUITY; FEMINISM; GENDER/EQUITY; SOCIAL JUSTICE
## 3 COLORBLIND RACISM; MENTORING; STUDENTS OF COLOR
## 4 AFRICAN-AMERICAN; SCIENCE IDENTITY; MATRICULATION; ACCESS TO SCIENCE
## 5 STEREOTYPE MANAGEMENT; STEM STUDENTS OF COLOR; RACIAL HOSTILITY IN ACADEMIA; STEM RACIAL GAP; CULTURAL BIAS
## 6 <NA>
## 7 CRITICAL PEDAGOGY; CULTURALLY RELEVANT SCIENCE; EQUITY IN SCIENCE EDUCATION; SECONDARY CHEMISTRY; SOCIAL JUSTICE
## 8 AFRICAN AMERICAN; FEMALE; FEMINISM; IDENTITY; INTERSECTIONALITY; STEM
## 9 SCIENCE EDUCATION; BLACK FACULTY; RACISM; HIGHER EDUCATION; CRITICAL RACE THEORY
## 10 RACISM; CAPITALISM; MATHEMATICS; SCIENCE; STEM; NEOLIBERALISM; EDUCATION
## 11 CRITICAL RACE THEORY; EQUITY; PRACTICES; SCIENCE TEACHING; SECONDARY
## 12 CRITICAL RACE THEORY; TEACHER EDUCATION; TEACHERS OF COLOR; SCIENCE EDUCATION; INTERSECTIONALITY
## 13 CULTURAL ANALYSIS; DISPARITIES; DOCTORAL; ENGINEERING EDUCATION; ENTREPRENEURSHIP; HBCUS; HIGHER EDUCATION; MENTORING; MINORITIZED; RACE; STEM; STRUCTURAL RACISM; TECHNOLOGY
## 14 RACIAL MICROAGGRESSIONS; HIGHER EDUCATION; STEM; EDUCATIONAL SETTING; DIVERSITY CONCERNS
## 15 RACE; PRESERVICE TEACHER EDUCATION; TEACHER NOTICING; EQUITY
## 16 RACE; GENDER; UNDERGRADUATES; QUALITATIVE RESEARCH
## 17 CRITICAL QUANTITATIVE INTERSECTIONALITY; EQUALITY; EQUITY; GENDER; HIERARCHICAL LINEAR MODEL; HIGHER EDUCATION; LEARNING; PHYSICS; RACE
## 18 ANTI-BLACKNESS; ANTI-RACIST TEACHING; EQUITY; POLITICAL CLARITY; ELEMENTARY STEM EDUCATION
## 19 <NA>
## 20 <NA>
## 21 SOCIAL JUSTICE; MIXED METHODS; QUALITATIVE METHODS; QUANTITATIVE METHODS; RACE; ETHNICITY; ADOLESCENCE
## 22 RACISM; RESISTANCE; WHITE SUPREMACY; ANTI-BLACKNESS; ECOLOGICAL SYSTEMS THEORIES; RACIAL SOCIALIZATION; ANTI-RACISM SOCIALIZATION; INTERSECTIONALITY; BLACK LIVES MATTER
## 23 PARTICIPATORY ACTION RESEARCH; YOUTH ACTIVISM; RACIAL JUSTICE; PANDEMIC
## 24 BLACK; MINORITY; WOMEN; STEM; COMMUNITY COLLEGE; TRANSFER; RACISM; SEXISM
## 25 <NA>
## 26 COLLEGE SCIENCE FACULTY; COLOR-BLIND RACISM; CRITICAL RACIAL CONSCIOUSNESS; RACIALLY MINORITIZED STUDENTS
## 27 BLACK STUDENTS; K-12 SCIENCE TEACHING; TEACHER EDUCATION; LIBERATION; ANTI-BLACKNESS
## 28 <NA>
## KeywordsPlus
## 1 CRITICAL RACE THEORY; AFRICAN-AMERICAN; RACIAL MICROAGGRESSIONS; TEST-PERFORMANCE; THREAT; IDENTITY; ACHIEVEMENT; EDUCATION; COLLEGE; GENDER
## 2 DISCURSIVE IDENTITY; FRAMEWORK; STUDENTS; PHYSICS; PARTICIPATION; CONSTRUCTION; EXPERIENCES; DISCOURSE; EDUCATION; LITERACY
## 3 COLLEGE-STUDENTS; AFRICAN-AMERICAN; GENDER; RACE; PERCEPTIONS; EXPERIENCES; WOMEN
## 4 EXPERIENCES; PERSISTENCE; STUDENTS
## 5 CRITICAL RACE THEORY; STEREOTYPE THREAT; SCIENCE; EXPERIENCES; EDUCATION; MICROAGGRESSIONS; MATHEMATICS; DIVERSITY; STUDENTS; COLOR
## 6 EDUCATING PROSPECTIVE TEACHERS; INQUIRY; BIOLOGY; RACISM; CONCEPTIONS; KNOWLEDGE; IDEOLOGY; IDENTITY; POVERTY; DESIGN
## 7 EDUCATION
## 8 RACE; GENDER; WOMEN; STUDENTS; COLOR; COMMUNITY; MOVEMENT
## 9 CAMPUS RACIAL CLIMATE; AFRICAN-AMERICANS; FACULTY; MICROAGGRESSIONS; SATISFACTION; EDUCATION; COLLEGES; WORKLIFE
## 10 MATHEMATICS
## 11 CRITICAL RACE THEORY; AMERICAN STUDENTS; MINORITY-STUDENTS; EDUCATION; EQUITY; MATHEMATICS; DIVERSITY; PERSPECTIVES; ACHIEVEMENT; PERSISTENCE
## 12 COLOR; PRESERVICE; WHITENESS; STUDENTS; MATHEMATICS; EXPERIENCES; IDENTITY; POLICIES
## 13 MATHEMATICS EDUCATION; COLOR; BLACK; RACE; SCIENCE; IDENTITY; STUDENTS; HEALTH; WOMEN; EXPERIENCES
## 14 AFRICAN-AMERICAN STUDENTS; CRITICAL RACE THEORY; PREDOMINANTLY WHITE; GENDER-DIFFERENCES; COLLEGE-STUDENTS; EXPERIENCES; CLIMATE; COLOR; STEREOTYPE; OPPORTUNITIES
## 15 RACIAL IDENTITY; DIVERSITY; PARTICIPATION; ATTITUDES; IDEOLOGY; COLOR; EDUCATION; CHILDREN; CULTURE; EQUITY
## 16 DOUBLE BIND; SCIENCE; WOMEN; RACE
## 17 GENDER
## 18 CRITICAL RACE THEORY; PEDAGOGY; STORIES; EQUITY; AGENCY
## 19 COLORADO LEARNING ATTITUDES; SELF-EFFICACY; WOMEN; GENDER; MODEL; IMPUTATION; BELIEFS
## 20 CRITICAL RACE; AGENCY; CURRICULUM; EDUCATION; RELEVANCE; PEDAGOGY; STUDENTS; CRITIQUE
## 21 <NA>
## 22 ETHNIC-RACIAL SOCIALIZATION; SOCIAL CONSTRUCTION; RACE SOCIALIZATION; COLOR-BLINDNESS; IDENTITY; PSYCHOLOGY; PERSPECTIVE; MINORITY; STEREOTYPES; PRECURSORS
## 23 PARTICIPATORY ACTION RESEARCH; COMMUNITY
## 24 FEMALE TRANSFER STUDENTS; HIGHER-EDUCATION; TRANSFER SHOCK; ACADEMIC-PERFORMANCE; CHILLY CLIMATE; DOUBLE BIND; COLOR; GENDER; SCIENCE; UNDERGRADUATE
## 25 CRITICAL RACE THEORY; MATHEMATICS; PERSISTENCE; IDENTITIES; BLACK; OPPORTUNITIES; PERCEPTIONS; EXPERIENCES; EDUCATION; IDEOLOGY
## 26 STUDENTS; WOMEN; RACE; UNDERGRADUATE; EDUCATION; RACISM; GAPS; ACHIEVEMENT; PERFORMANCE; PERSISTENCE
## 27 RACE; STEM; EQUITY; CONSTRUCTION; MATHEMATICS; AMERICANS; PIPELINE; IDENTITY; STUDENTS; JUSTICE
## 28 HIGHER-EDUCATION; RACISM; COLOR; MATHEMATICS; STUDENTS; EXPERIENCES; IDEOLOGY; CLIMATE; WOMEN
## DOI Year LCS GCS
## 1 10.3102/0002831211423972 2011 16 289
## 2 10.1002/tea.20411 2011 4 146
## 3 10.1037/a0038676 2015 7 79
## 4 10.1002/tea.21249 2016 5 59
## 5 10.3102/0002831216676572 2016 18 193
## 6 10.1080/07370008.2016.1215721 2016 5 17
## 7 10.1002/sce.21305 2017 7 125
## 8 10.1080/1046560X.2018.1436359 2018 2 6
## 9 10.1007/s11422-016-9774-0 2018 2 9
## 10 10.1080/13613324.2019.1592840 2019 2 25
## 11 10.1002/sce.21450 2019 12 56
## 12 10.3102/0002831218818093 2019 6 40
## 13 10.3102/0013189X20972718 2020 14 171
## 14 10.1186/s40594-020-00241-4 2020 3 54
## 15 10.1177/0022487119900204 2020 3 56
## 16 10.1186/s40594-020-00250-3 2020 2 18
## 17 10.1002/tea.21584 2020 3 44
## 18 10.1007/s42330-021-00159-1 2021 4 22
## 19 10.1103/PhysRevPhysEducRes.17.010116 2021 2 27
## 20 10.1080/07370008.2020.1828421 2021 3 22
## 21 10.1177/07435584211031450 2021 2 11
## 22 10.1159/000519630 2021 3 59
## 23 10.1177/07435584211034873 2021 2 9
## 24 10.1186/s40594-022-00334-2 2022 2 11
## 25 10.1080/10508406.2022.2073233 2022 2 4
## 26 10.1002/tea.21775 2022 2 11
## 27 10.1080/1046560X.2021.2008096 2022 2 16
## 28 10.1187/cbe.22-06-0104 2023 2 10
NetMatrix1 <- biblioNetwork(M1_dup,
analysis = "co-occurrences",
network = "keywords",
sep = ";")
net1=networkPlot(NetMatrix1,
normalize="association",
n = 50,
Title = "Keyword Co-occurrences",
type = "fruchterman",
size.cex=TRUE,
size=20,
remove.multiple=F,
edgesize = 10,
labelsize=5,
label.cex=TRUE,
label.n=30,
edges.min=2)
NetMatrix2 <- biblioNetwork(M2_dup,
analysis = "co-occurrences",
network = "keywords",
sep = ";")
net2=networkPlot(NetMatrix2,
normalize="association",
n = 50,
Title = "Keyword Co-occurrences",
type = "fruchterman",
size.cex=TRUE,
size=20,
remove.multiple=F,
edgesize = 10,
labelsize=5,
label.cex=TRUE,
label.n=30,
edges.min=2)
NetMatrix3 <- biblioNetwork(M3_dup,
analysis = "co-occurrences",
network = "keywords",
sep = ";")
net3=networkPlot(NetMatrix3,
normalize="association",
n = 50,
Title = "Keyword Co-occurrences",
type = "fruchterman",
size.cex=TRUE,
size=20,
remove.multiple=F,
edgesize = 10,
labelsize=5,
label.cex=TRUE,
label.n=30,
edges.min=2)
Descriptive analysis of the keyword co-occurence network characteristics.
netstat1 <- networkStat(NetMatrix1)
summary(netstat1, k=10)
##
##
## Main statistics about the network
##
## Size 425
## Density 0.034
## Transitivity 0.261
## Diameter 5
## Degree Centralization 0.346
## Average path length 2.444
##
netstat2 <- networkStat(NetMatrix2)
summary(netstat2, k=10)
##
##
## Main statistics about the network
##
## Size 352
## Density 0.033
## Transitivity 0.374
## Diameter 6
## Degree Centralization 0.201
## Average path length 2.812
##
netstat3 <- networkStat(NetMatrix3)
summary(netstat3, k=10)
##
##
## Main statistics about the network
##
## Size 626
## Density 0.023
## Transitivity 0.243
## Diameter 5
## Degree Centralization 0.301
## Average path length 2.623
##
suppressWarnings(CS1 <- conceptualStructure(M1,
method="MCA",
field="ID",
minDegree=15,
clust=5,
stemming=FALSE,
labelsize=15,
documents=20)
)
suppressWarnings(CS2 <- conceptualStructure(M2,
method="MCA",
field="ID",
minDegree=15,
clust=4,
stemming=FALSE,
labelsize=15,
documents=20)
)
suppressWarnings(CS3 <- conceptualStructure(M3,
method="MCA",
field="ID",
minDegree=15,
clust=4,
stemming=FALSE,
labelsize=15,
documents=20)
)
Map1=thematicMap(M1, field = "ID", n = 250, minfreq = 10,
stemming = FALSE, size = 0.7, n.labels=5, repel = TRUE)
plot(Map1$map)
Map2=thematicMap(M2, field = "ID", n = 250, minfreq = 15,
stemming = FALSE, size = 0.7, n.labels=5, repel = TRUE)
plot(Map2$map)
Map3=thematicMap(M3, field = "ID", n = 250, minfreq = 15,
stemming = FALSE, size = 0.7, n.labels=5, repel = TRUE)
plot(Map3$map)
Clusters1=Map1$words[order(Map1$words$Cluster,-Map1$words$Occurrences),]
Clusters2=Map2$words[order(Map2$words$Cluster,-Map2$words$Occurrences),]
Clusters3=Map3$words[order(Map3$words$Cluster,-Map3$words$Occurrences),]
CL1 <- Clusters1 %>% group_by(.data$Cluster_Label) %>% top_n(5, .data$Occurrences)
CL1
## # A tibble: 26 × 9
## # Groups: Cluster_Label [10]
## Occurrences Words Cluster Color Cluster_Label Cluster_Frequency btw_centrality clos_centrality pagerank_centrality
## <dbl> <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 6 beliefs 1 #E41A1C80 beliefs 6 257. 0.000898 0.00287
## 2 26 equity 2 #4DAF4A80 equity 320 847. 0.00104 0.0114
## 3 26 school 2 #4DAF4A80 equity 320 785. 0.00102 0.0113
## 4 26 teachers 2 #4DAF4A80 equity 320 716. 0.000940 0.0104
## 5 24 knowledge 2 #4DAF4A80 equity 320 846. 0.00103 0.0107
## 6 20 pedagogy 2 #4DAF4A80 equity 320 692. 0.00101 0.00848
## 7 114 race 3 #984EA380 race 1098 3565. 0.00112 0.0382
## 8 98 students 3 #984EA380 race 1098 2893. 0.00115 0.0375
## 9 90 education 3 #984EA380 race 1098 1706. 0.00105 0.0355
## 10 72 science 3 #984EA380 race 1098 1095. 0.00100 0.0254
## # ℹ 16 more rows
CL2 <- Clusters2 %>% group_by(.data$Cluster_Label) %>% top_n(5, .data$Occurrences)
CL2
## # A tibble: 46 × 9
## # Groups: Cluster_Label [14]
## Occurrences Words Cluster Color Cluster_Label Cluster_Frequency btw_centrality clos_centrality pagerank_centrality
## <dbl> <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 26 discrimination 1 #E41A1… discriminati… 232 1791. 0.000947 0.0225
## 2 20 african-american 1 #E41A1… discriminati… 232 1906. 0.000978 0.0185
## 3 16 health 1 #E41A1… discriminati… 232 2060. 0.00101 0.0134
## 4 16 identity 1 #E41A1… discriminati… 232 2087. 0.00101 0.0140
## 5 12 socialization 1 #E41A1… discriminati… 232 494. 0.000901 0.0119
## 6 12 youth 1 #E41A1… discriminati… 232 822. 0.000926 0.0107
## 7 6 curriculum 2 #377EB… curriculum 6 370. 0.000785 0.00478
## 8 4 age 3 #4DAF4… age 4 208. 0.000796 0.00410
## 9 6 inclusion 4 #984EA… inclusion 34 251. 0.000745 0.00577
## 10 4 biology 4 #984EA… inclusion 34 292. 0.000832 0.00485
## # ℹ 36 more rows
CL3 <- Clusters3 %>% group_by(.data$Cluster_Label) %>% top_n(5, .data$Occurrences)
CL3
## # A tibble: 13 × 9
## # Groups: Cluster_Label [5]
## Occurrences Words Cluster Color Cluster_Label Cluster_Frequency btw_centrality clos_centrality pagerank_centrality
## <dbl> <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 12 disparities 1 #377EB… disparities 12 541. 0.000864 0.00449
## 2 38 african-american 2 #4DAF4… african-amer… 216 718. 0.000969 0.0128
## 3 38 discrimination 2 #4DAF4… african-amer… 216 677. 0.000963 0.0144
## 4 30 health 2 #4DAF4… african-amer… 216 584. 0.000951 0.00875
## 5 22 youth 2 #4DAF4… african-amer… 216 477. 0.000963 0.00800
## 6 18 mental-health 2 #4DAF4… african-amer… 216 645. 0.000982 0.00693
## 7 150 race 3 #984EA… race 1582 2606. 0.00105 0.0342
## 8 112 students 3 #984EA… race 1582 1999. 0.00106 0.0305
## 9 98 education 3 #984EA… race 1582 1253. 0.000986 0.0280
## 10 94 experiences 3 #984EA… race 1582 1415. 0.00101 0.0315
## 11 94 science 3 #984EA… race 1582 765. 0.000973 0.0224
## 12 12 bias 4 #A6562… bias 12 92.0 0.000826 0.00314
## 13 12 conceptions 5 #F781B… conceptions 12 109. 0.000836 0.00521
threeFieldsPlot(M1_dup, fields = c("DE", "AU", "AU_CO"))
threeFieldsPlot(M2_dup, fields = c("DE", "AU", "AU_CO"))
threeFieldsPlot(M3_dup, fields = c("DE", "AU", "AU_CO"))
threeFieldsPlot(M1_dup, fields = c("DE", "ID", "SO"))
threeFieldsPlot(M2_dup, fields = c("DE", "ID", "SO"))
threeFieldsPlot(M3_dup, fields = c("DE", "ID", "SO"))
Subset study data from M3 data frame to conduct additional analyses to extract meaning from data.
Create corpus objects of abstracts (AB) in each of the data frames. Generate tokens for each term in the abstracts. Identify the keywords-in-context for selected studies. We also remove stopwords.
## Package version: 4.0.1
## Unicode version: 14.0
## ICU version: 71.1
## Parallel computing: disabled
## See https://quanteda.io for tutorials and examples.
##
## Attaching package: 'quanteda'
## The following object is masked from 'package:readtext':
##
## texts
## Corpus consisting of 351 documents.
## text1 :
## "THE RACIALIZED STRUCTURE OF STEM (SCIENCE, TECHNOLOGY, ENGIN..."
##
## text2 :
## "IF WE ENVISION A FUTURE FOR BLACK YOUNG LEARNERS WHERE THEIR..."
##
## text3 :
## "A GROUP OF 3 AFRICAN AMERICAN FEMALE PRESERVICE SCIENCE AND ..."
##
## text4 :
## "TEACHERS INVOLVED IN A MASTER'S LEVEL COURSE IN DIVERSITY PA..."
##
## text5 :
## "INSPIRED BY THE BIOLOGY EDUCATION RESEARCH COMMUNITY'S COLLE..."
##
## text6 :
## "AGAINST A BACKDROP OF CALLS FOR INCREASED ACCESS AND PARTICI..."
##
## [ reached max_ndoc ... 345 more documents ]
We use the keywords in context to gather the final component for the notions (concepts) (see fig. 1).
toks <- M3_corp_abstract %>%
corpus_subset() %>%
tokens()
racism <- c("Racism")
head(kwic(toks, pattern = phrase(racism)))
## Keyword-in-context with 6 matches.
## [text1, 25] THAT ARE ILLUSTRATIVE OF STRUCTURAL | RACISM | , WHICH BOTH INFORMS AND
## [text1, 52] , AN EXAMINATION INTO STRUCTURAL | RACISM | IN STEM IS NEEDED TO
## [text1, 84] THAT ALLOW THE FOUNDATION OF | RACISM | TO REMAIN INTACT. I
## [text1, 179] CRITICAL EXAMINATION OF THE STRUCTURAL | RACISM | OMNIPRESENT IN THE STEM,
## [text2, 41] , WE MUST DISRUPT SYSTEMIC | RACISM | NOW. IN THIS ARTICLE
## [text2, 73] TEACHER EDUCATORS MUST DISRUPT ANTI-BLACK | RACISM | IN OUR WORK WITH ELEMENTARY
tail(kwic(toks, pattern = phrase(racism)))
## Keyword-in-context with 6 matches.
## [text343, 84] , SYSTEMIC PROBLEMS SUCH AS | RACISM | AND POVERTY INCREASE THE RISK
## [text347, 216] WHITE AMERICANS. THE MODERN | RACISM | SCALE ( MRS ) IS
## [text348, 56] HATE, OFFENSIVE LANGUAGE, | RACISM | , SEXUAL CONTENT, AND
## [text349, 290] VERTEBRATE ANATOMY NEEDS TO ACKNOWLEDGE | RACISM | , ANDROCENTRISM, HOMOPHOBIA,
## [text350, 13] ALSO KNOWN AS" SEXUAL | RACISM | ," IS AN UNDERSTUDIED
## [text351, 129] E-MAILS, INCLUDING SEXISM, | RACISM | , AND THREATENING, AND
racist <- c("Racist")
head(kwic(toks, pattern = phrase(racist)))
## Keyword-in-context with 6 matches.
## [text1, 113] DEGREE HOLDERS CONSISTENTLY ENDURE THE | RACIST | RESIDUE OF HIGHER EDUCATION INSTITUTIONS
## [text5, 37] IDENTIFIED BY KENDI AS PERPETUATING | RACIST | IDEAS. AT THE SAME
## [text18, 159] FOR THEMSELVES AND STUDENTS WITHIN | RACIST | EDUCATIONAL STRUCTURES AND SYSTEMS.
## [text20, 30] , THIS CRITICISM TAKES A | RACIST | FORM AS IT IS FREQUENTLY
## [text20, 58] IN WHICH ITAS WORK INFLUENCE | RACIST | PERCEPTIONS OF AND EXPECTATIONS ABOUT
## [text23, 262] STRATEGIC INVENTIONS WHICH DISMANTLE THE | RACIST | , SEXIST, CLASSIST,
tail(kwic(toks, pattern = phrase(racist)))
## Keyword-in-context with 6 matches.
## [text303, 16] SYSTEM THAT PERPETUATES SEXIST AND | RACIST | " REWARDS" BY PRIORITIZING
## [text320, 179] EXPLOITATIVE, AUTHORITARIAN, AND | RACIST | FORCES OF BIOPOWER, THE
## [text334, 99] THE WIDESPREAD PRACTICE OF USING | RACIST | AND STEREOTYPICAL RHETORIC IN GSD
## [text339, 150] IN PERPETUATING DISCRIMINATION AND ELIMINATING | RACIST | BEHAVIOURS. AS SUCH,
## [text345, 154] " SPEAKS BACK" TO | RACIST | PRACTICES AND ENTRENCHED BARRIERS THAT
## [text346, 307] TO THE NEED TO END | RACIST | / SEXIST TREATMENT OF WOMEN
racism.kw <- c("Structural Racism", "Systemic Racism", "Racis*")
head(kwic(toks, pattern = phrase(racism.kw)))
## Keyword-in-context with 6 matches.
## [text1, 24:25] INEQUITIES THAT ARE ILLUSTRATIVE OF | STRUCTURAL RACISM | , WHICH BOTH INFORMS AND
## [text1, 25:25] THAT ARE ILLUSTRATIVE OF STRUCTURAL | RACISM | , WHICH BOTH INFORMS AND
## [text1, 51:52] THUS, AN EXAMINATION INTO | STRUCTURAL RACISM | IN STEM IS NEEDED TO
## [text1, 52:52] , AN EXAMINATION INTO STRUCTURAL | RACISM | IN STEM IS NEEDED TO
## [text1, 84:84] THAT ALLOW THE FOUNDATION OF | RACISM | TO REMAIN INTACT. I
## [text1, 113:113] DEGREE HOLDERS CONSISTENTLY ENDURE THE | RACIST | RESIDUE OF HIGHER EDUCATION INSTITUTIONS
tail(kwic(toks, pattern = phrase(racism.kw)))
## Keyword-in-context with 6 matches.
## [text346, 307] TO THE NEED TO END | RACIST | / SEXIST TREATMENT OF WOMEN
## [text347, 216] WHITE AMERICANS. THE MODERN | RACISM | SCALE ( MRS ) IS
## [text348, 56] HATE, OFFENSIVE LANGUAGE, | RACISM | , SEXUAL CONTENT, AND
## [text349, 290] VERTEBRATE ANATOMY NEEDS TO ACKNOWLEDGE | RACISM | , ANDROCENTRISM, HOMOPHOBIA,
## [text350, 13] ALSO KNOWN AS" SEXUAL | RACISM | ," IS AN UNDERSTUDIED
## [text351, 129] E-MAILS, INCLUDING SEXISM, | RACISM | , AND THREATENING, AND
black <- c("Black", "African-American", "African American")
head(kwic(toks, pattern = phrase(black)))
## Keyword-in-context with 6 matches.
## [text1, 102:102] OF THE EDUCATION HIERARCHY, | BLACK | STEM DOCTORATE STUDENTS AND PHD
## [text2, 7:7] WE ENVISION A FUTURE FOR | BLACK | YOUNG LEARNERS WHERE THEIR FULL
## [text2, 165:165] ASSIGNMENTS, AND EXPERIENCES AS | BLACK | WOMEN EDUCATORS AND TEACHER EDUCATORS
## [text3, 5:6] A GROUP OF 3 | AFRICAN AMERICAN | FEMALE PRESERVICE SCIENCE AND SCIENCE
## [text7, 30:30] ECONOMIC OPPORTUNITIES. YET, | BLACK | STUDENTS HAVE BEEN EXCLUDED FROM
## [text7, 57:57] THIS ARTICLE REVIEWS RESEARCH ON | BLACK | STUDENT MATHEMATICS PARTICIPATION AT THE
tail(kwic(toks, pattern = phrase(black)))
## Keyword-in-context with 6 matches.
## [text333, 175] ADDRESS VIOLENCE IN THEIR PREDOMINANTLY | BLACK | COMMUNITIES. WE: (
## [text333, 250] EXAMINE THE WAYS IN WHICH | BLACK | PEOPLE ARE SUBJUGATED, SURVEILLED
## [text338, 9] ANALYSIS OF THE CIRCUMSTANCES OF | AFRICAN-AMERICAN | BOYS AND YOUNG MEN (
## [text347, 131] SUBJECTS, AMYGDALA ACTIVATION TO | BLACK | VERSUS WHITE FACES WAS CORRELATED
## [text347, 290] AND A NEGATIVE EVALUATION TOWARDS | BLACK | FACES ON THE INDIRECT MEASURE
## [text347, 312] EVEN THOUGH AMYGDALA ACTIVATION TO | BLACK | VERSUS WHITE FACES IS CORRELATED
white <- c("Whiteness", "White Supremacy")
head(kwic(toks, pattern = phrase(white)))
## Keyword-in-context with 6 matches.
## [text12, 43] HAVE HISTORICALLY PRIVILEGED MEN AND | WHITENESS | . PARTICIPANT NARRATIVES GAINED THROUGH
## [text34, 179] FINDING, WHICH WAS THAT | WHITENESS | WAS EXPRESSED THROUGH KATHERINE'S ACADEMIC
## [text34, 218] A CULTURAL PRODUCT THAT REFLECTS | WHITENESS | AS A CULTURAL NORM.
## [text50, 9] THE EMBODIMENT AND AFFECTIVITY OF | WHITENESS | , PARTICULARLY AS IT IMPLICATES
## [text50, 35] WHAT WAYS ARE AFFECT AND | WHITENESS | CONSTITUTIVE OF EACH OTHER IN
## [text50, 67] THIS ENTANGLEMENT? IN THEORIZING | WHITENESS | AS A TECHNOLOGY OF AFFECT
tail(kwic(toks, pattern = phrase(white)))
## Keyword-in-context with 6 matches.
## [text313, 77:78] ARE NECESSARY TO CHALLENGE HOW | WHITE SUPREMACY | CULTURE SHAPES SOCIAL SCIENCE RESEARCH
## [text314, 26:27] AND REIFY SETTLER COLONIALISM AND | WHITE SUPREMACY | , THIS ARTICLE CALLS FOR
## [text314, 69:70] NATURE OF SETTLER COLONIALISM, | WHITE SUPREMACY | , AND THE CONSTRUCTS OF
## [text324, 105:106] , COLONIALISM, RACISM AND | WHITE SUPREMACY | , PATRIARCHY, AND ABLEISM
## [text333, 305:305] AND COLORBLINDNESS THAT CENTERS ON | WHITENESS | , INNOVATION, AND CAPITALISM
## [text339, 133:133] EDUCATION, BECOMING CONSCIOUS OF | WHITENESS | AND LOOKING CRITICALLY AT MYSELF
mov <- c("Antiblackness", "Anti-Blackness", "Coloniality", "Colonialism")
head(kwic(toks, pattern = phrase(mov)))
## Keyword-in-context with 6 matches.
## [text2, 50] THIS ARTICLE WE DISCUSS HOW | ANTI-BLACKNESS | IS PERVASIVE IN SCIENCE AND
## [text2, 95] DO THIS WORK AND DISRUPT | ANTI-BLACKNESS | , ELEMENTARY TEACHER EDUCATORS AND
## [text16, 202] AIMS TO COUNTER COLOR-EVASIVENESS AND | ANTI-BLACKNESS | IN TEACHING. FURTHERMORE,
## [text59, 110] OF BLACKS, IT REINFORCED | ANTI-BLACKNESS | . I END WITH A
## [text68, 42] THE RESULT BROADLY OF SETTLER | COLONIALISM | , AND MORE SPECIFICALLY OF
## [text72, 43] , RACISM, CISHETEROPATRIARCHY, | COLONIALISM | ) SHAPE VARIATION IN STRUCTURAL
tail(kwic(toks, pattern = phrase(mov)))
## Keyword-in-context with 6 matches.
## [text301, 18] PERPETUATE ) WHITE SUPREMACY AND | ANTI-BLACKNESS | . WHILE HUMAN DEVELOPMENT IS
## [text314, 24] BUILD UPON AND REIFY SETTLER | COLONIALISM | AND WHITE SUPREMACY, THIS
## [text314, 67] THE CONSTITUTIVE NATURE OF SETTLER | COLONIALISM | , WHITE SUPREMACY, AND
## [text314, 116] RELATED TO DISRUPTING ONGOING SETTLER | COLONIALISM | , ENGAGING IN CULTURALLY HUMBLE
## [text324, 101] AS CAPITALISM AND CLASSISM, | COLONIALISM | , RACISM AND WHITE SUPREMACY
## [text332, 89] DISTRIBUTIONS OF POWER SHAPED BY | COLONIALISM | , ( B ) CHALLENGING
STEM <- c("STEM")
head(kwic(toks, pattern = phrase(STEM)))
## Keyword-in-context with 6 matches.
## [text1, 5] THE RACIALIZED STRUCTURE OF | STEM | ( SCIENCE, TECHNOLOGY,
## [text1, 54] EXAMINATION INTO STRUCTURAL RACISM IN | STEM | IS NEEDED TO EXPOSE THE
## [text1, 65] MARGINALIZATION OF UNDERREPRESENTED GROUPS IN | STEM | AND TO IMPROVE UNDERSTANDING OF
## [text1, 72] TO IMPROVE UNDERSTANDING OF THE | STEM | POLICIES, PRACTICES, AND
## [text1, 103] THE EDUCATION HIERARCHY, BLACK | STEM | DOCTORATE STUDENTS AND PHD DEGREE
## [text1, 120] OF HIGHER EDUCATION INSTITUTIONS AND | STEM | EMPLOYERS. THUS, THIS
tail(kwic(toks, pattern = phrase(STEM)))
## Keyword-in-context with 6 matches.
## [text261, 294] IDENTIFICATION AS A WOMAN IN | STEM | WAS STRONGER COMPARED TO INSTANCES
## [text261, 372] RECRUIT AND RETAIN WOMEN IN | STEM | , AS WELL AS THE
## [text266, 272] DISTRIBUTION OR STEREOTYPES SUCH AS | STEM | ( SCIENCE, TECHNOLOGY,
## [text298, 26] ETHNIC-RACIAL MINORITY ACCESS TO HIGH-ACHIEVING | STEM | SCHOOLS. WE CONDUCTED AN
## [text298, 85] SOCIOECONOMIC STATUS, AND HIGHER | STEM | PRESTIGE-EVIDENCE OF GATEKEEPING POINTS TO
## [text298, 98] OF ASIAN STUDENTS FROM ADVANCED | STEM | OPPORTUNITIES. RESULTS ARE SITUATED
# kwic(toks_M3_corp_abstract, pattern = "racism") %>% textplot_xray()
comp_str_racism_toks <- tokens_compound(toks, pattern = phrase("Structural Racism"))
head(tokens_select(comp_str_racism_toks, pattern = c("Structural_Racism")))
## Tokens consisting of 6 documents.
## text1 :
## [1] "STRUCTURAL_RACISM" "STRUCTURAL_RACISM" "STRUCTURAL_RACISM"
##
## text2 :
## character(0)
##
## text3 :
## character(0)
##
## text4 :
## character(0)
##
## text5 :
## character(0)
##
## text6 :
## character(0)
tail(tokens_select(comp_str_racism_toks, pattern = c("Structural_Racism")))
## Tokens consisting of 6 documents.
## text346 :
## character(0)
##
## text347 :
## character(0)
##
## text348 :
## character(0)
##
## text349 :
## character(0)
##
## text350 :
## character(0)
##
## text351 :
## character(0)
Remove punctuation and stop words.
toks <- M3_corp_abstract %>%
corpus_subset() %>%
tokens(remove_punct = T) %>%
tokens_remove(pattern = stopwords('english')) %>%
tokens()
toks
## Tokens consisting of 351 documents.
## text1 :
## [1] "RACIALIZED" "STRUCTURE" "STEM" "SCIENCE" "TECHNOLOGY" "ENGINEERING" "MATHEMATICS" "HIGHER" "EDUCATION"
## [10] "MAINTAINS" "GROSS" "INEQUITIES"
## [ ... and 97 more ]
##
## text2 :
## [1] "ENVISION" "FUTURE" "BLACK" "YOUNG" "LEARNERS" "FULL" "HUMANITY" "HONOURED" "EDUCATORS"
## [10] "FACILITATE" "RIGOROUS" "SCIENCE"
## [ ... and 116 more ]
##
## text3 :
## [1] "GROUP" "3" "AFRICAN" "AMERICAN" "FEMALE" "PRESERVICE" "SCIENCE" "SCIENCE" "TEACHING"
## [10] "STUDENTS" "MAJORING" "FIELD"
## [ ... and 60 more ]
##
## text4 :
## [1] "TEACHERS" "INVOLVED" "MASTER'S" "LEVEL" "COURSE" "DIVERSITY" "PARTICIPATED" "VIRTUAL"
## [9] "SYNCHRONOUS" "ANONYMIZED" "DISCUSSIONS" "AROUND"
## [ ... and 117 more ]
##
## text5 :
## [1] "INSPIRED" "BIOLOGY" "EDUCATION" "RESEARCH" "COMMUNITY'S" "COLLECTIVE" "READING" "KENDI'S" "ANTIRACIST"
## [10] "DRAW" "TOGETHER" "RECENT"
## [ ... and 51 more ]
##
## text6 :
## [1] "BACKDROP" "CALLS" "INCREASED" "ACCESS" "PARTICIPATION" "SCIENCE"
## [7] "TECHNOLOGY" "ENGINEERING" "MATHEMATICS" "HISPANIC-SERVING" "INSTITUTIONS" "HSIS"
## [ ... and 114 more ]
##
## [ reached max_ndoc ... 345 more documents ]
toks_M3_corp_abstract <- corpus_subset(M3_corp_abstract) %>%
tokens(remove_punct = TRUE) %>%
tokens_remove(pattern = stopwords('english')) %>%
tokens()
dfm_rel_freq <- dfm_weight(dfm(toks_M3_corp_abstract), scheme = "prop") * 100
head(dfm_rel_freq)
## Document-feature matrix of: 6 documents, 7,525 features (98.94% sparse) and 0 docvars.
## features
## docs racialized structure stem science technology engineering mathematics higher education maintains
## text1 0.9174312 0.9174312 8.2568807 0.9174312 0.9174312 0.9174312 0.9174312 1.834862 2.752294 0.9174312
## text2 0 0 2.3437500 2.3437500 0.7812500 0.7812500 2.3437500 0 1.562500 0
## text3 0 0 5.5555556 4.1666667 1.3888889 1.3888889 1.3888889 0 0 0
## text4 0 0 2.3255814 3.1007752 0.7751938 0.7751938 3.1007752 0 0 0
## text5 0 0 3.1746032 1.5873016 1.5873016 1.5873016 1.5873016 0 3.174603 0
## text6 0 0 0.7936508 1.5873016 0.7936508 3.9682540 0.7936508 0 0 0
## [ reached max_nfeat ... 7,515 more features ]
# frequency plots
dfmat_racism_stem <- corpus_subset(M3_corp_abstract) |>
tokens(remove_punct = TRUE) |>
tokens_remove(pattern = stopwords('english')) |>
dfm() |>
dfm_trim(min_termfreq = 10, verbose = FALSE)
set.seed(3)
textplot_wordcloud(dfmat_racism_stem)
Text stats frequency
# text stats frequency
tstat_freq_racism_stem <- textstat_frequency(dfmat_racism_stem, n = 100)
ggplot(tstat_freq_racism_stem, aes(x = frequency, y = reorder(feature, frequency))) +
geom_point() +
labs(x = "Frequency", y = "Feature")
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Howard University, nathan.alexander@howard.edu↩︎
Howard University, qyana.stewart@howard.edu↩︎
Howard University, basil.ghali@howard.edu↩︎